From f41d51b0bc05550e91bb8ace0f02c6504b1e8aae Mon Sep 17 00:00:00 2001
From: timbeechey <66388815+timbeechey@users.noreply.github.com>
Date: Thu, 15 Feb 2024 13:15:52 +0000
Subject: [PATCH] =?UTF-8?q?Deploying=20to=20gh-pages=20from=20@=20timbeech?=
 =?UTF-8?q?ey/opa@5c0988a60a3b63482a42e0b4e7ed1ce511cda56c=20=F0=9F=9A=80?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 404.html                                       | 2 +-
 LICENSE.html                                   | 2 +-
 articles/index.html                            | 2 +-
 articles/opa.html                              | 2 +-
 authors.html                                   | 6 +++---
 index.html                                     | 2 +-
 pkgdown.yml                                    | 2 +-
 reference/compare_conditions.html              | 2 +-
 reference/compare_groups.html                  | 2 +-
 reference/compare_hypotheses.html              | 2 +-
 reference/correct_pairs.html                   | 2 +-
 reference/cval_plot.html                       | 2 +-
 reference/group_cvals.html                     | 2 +-
 reference/group_pccs.html                      | 2 +-
 reference/group_results.html                   | 2 +-
 reference/hypothesis.html                      | 2 +-
 reference/incorrect_pairs.html                 | 2 +-
 reference/index.html                           | 2 +-
 reference/individual_cvals.html                | 2 +-
 reference/individual_pccs.html                 | 2 +-
 reference/individual_results.html              | 2 +-
 reference/opa.html                             | 2 +-
 reference/pcc_plot.html                        | 2 +-
 reference/plot.opafit.html                     | 2 +-
 reference/plot.opahypothesis.html              | 2 +-
 reference/print.opaGroupComparison.html        | 2 +-
 reference/print.opaHypothesisComparison.html   | 2 +-
 reference/print.opafit.html                    | 2 +-
 reference/print.opahypothesis.html             | 2 +-
 reference/print.pairwiseopafit.html            | 2 +-
 reference/random_pccs.html                     | 2 +-
 reference/summary.opaGroupComparison.html      | 2 +-
 reference/summary.opaHypothesisComparison.html | 2 +-
 reference/summary.opafit.html                  | 2 +-
 search.json                                    | 2 +-
 35 files changed, 37 insertions(+), 37 deletions(-)

diff --git a/404.html b/404.html
index 23bb4c3..a9b6fd3 100644
--- a/404.html
+++ b/404.html
@@ -24,7 +24,7 @@
     
     <a class="navbar-brand me-2" href="https://timbeechey.github.io/opa/index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/LICENSE.html b/LICENSE.html
index 064afba..7c58025 100644
--- a/LICENSE.html
+++ b/LICENSE.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/articles/index.html b/articles/index.html
index 3d5850b..5a5f30b 100644
--- a/articles/index.html
+++ b/articles/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/articles/opa.html b/articles/opa.html
index 70bb570..bd829a3 100644
--- a/articles/opa.html
+++ b/articles/opa.html
@@ -26,7 +26,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/authors.html b/authors.html
index 7ee4fd8..9eea2a0 100644
--- a/authors.html
+++ b/authors.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@@ -58,13 +58,13 @@ <h2 id="citation">Citation</h2>
 
       <p>Beechey T (2024).
 <em>opa: An Implementation of Ordinal Pattern Analysis</em>.
-R package version 0.8.1.025, <a href="https://timbeechey.github.io/opa/">https://timbeechey.github.io/opa/</a>. 
+R package version 0.8.1.026, <a href="https://timbeechey.github.io/opa/">https://timbeechey.github.io/opa/</a>. 
 </p>
       <pre>@Manual{,
   title = {opa: An Implementation of Ordinal Pattern Analysis},
   author = {Timothy Beechey},
   year = {2024},
-  note = {R package version 0.8.1.025},
+  note = {R package version 0.8.1.026},
   url = {https://timbeechey.github.io/opa/},
 }</pre>
     </div>
diff --git a/index.html b/index.html
index 17221bb..e1db56a 100644
--- a/index.html
+++ b/index.html
@@ -36,7 +36,7 @@
     
     <a class="navbar-brand me-2" href="index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/pkgdown.yml b/pkgdown.yml
index f125d33..ae70923 100644
--- a/pkgdown.yml
+++ b/pkgdown.yml
@@ -3,7 +3,7 @@ pkgdown: 2.0.7
 pkgdown_sha: ~
 articles:
   opa: opa.html
-last_built: 2024-02-15T13:06Z
+last_built: 2024-02-15T13:15Z
 urls:
   reference: https://timbeechey.github.io/opa/reference
   article: https://timbeechey.github.io/opa/articles
diff --git a/reference/compare_conditions.html b/reference/compare_conditions.html
index 4baf1e8..33faeb3 100644
--- a/reference/compare_conditions.html
+++ b/reference/compare_conditions.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/compare_groups.html b/reference/compare_groups.html
index 29fb2a5..252a6e4 100644
--- a/reference/compare_groups.html
+++ b/reference/compare_groups.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/compare_hypotheses.html b/reference/compare_hypotheses.html
index edef9f9..92c00bb 100644
--- a/reference/compare_hypotheses.html
+++ b/reference/compare_hypotheses.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/correct_pairs.html b/reference/correct_pairs.html
index 2db67b0..494dced 100644
--- a/reference/correct_pairs.html
+++ b/reference/correct_pairs.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/cval_plot.html b/reference/cval_plot.html
index 6788fa3..6f56398 100644
--- a/reference/cval_plot.html
+++ b/reference/cval_plot.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/group_cvals.html b/reference/group_cvals.html
index 1a58c27..70fa7cf 100644
--- a/reference/group_cvals.html
+++ b/reference/group_cvals.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/group_pccs.html b/reference/group_pccs.html
index ee1b2e6..0b1fed2 100644
--- a/reference/group_pccs.html
+++ b/reference/group_pccs.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/group_results.html b/reference/group_results.html
index 09abbb2..b70491e 100644
--- a/reference/group_results.html
+++ b/reference/group_results.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/hypothesis.html b/reference/hypothesis.html
index 4b704f7..525337f 100644
--- a/reference/hypothesis.html
+++ b/reference/hypothesis.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/incorrect_pairs.html b/reference/incorrect_pairs.html
index 4b5921f..70eb1ce 100644
--- a/reference/incorrect_pairs.html
+++ b/reference/incorrect_pairs.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/index.html b/reference/index.html
index bad1e52..0195441 100644
--- a/reference/index.html
+++ b/reference/index.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/individual_cvals.html b/reference/individual_cvals.html
index 8291ec5..aa30e36 100644
--- a/reference/individual_cvals.html
+++ b/reference/individual_cvals.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/individual_pccs.html b/reference/individual_pccs.html
index 6f5f8ec..923739d 100644
--- a/reference/individual_pccs.html
+++ b/reference/individual_pccs.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/individual_results.html b/reference/individual_results.html
index 2bf6798..6d8db29 100644
--- a/reference/individual_results.html
+++ b/reference/individual_results.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/opa.html b/reference/opa.html
index c8d1fbb..80129aa 100644
--- a/reference/opa.html
+++ b/reference/opa.html
@@ -16,7 +16,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/pcc_plot.html b/reference/pcc_plot.html
index 00ba2fd..0c0217e 100644
--- a/reference/pcc_plot.html
+++ b/reference/pcc_plot.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/plot.opafit.html b/reference/plot.opafit.html
index 9e91d6f..539bd2b 100644
--- a/reference/plot.opafit.html
+++ b/reference/plot.opafit.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/plot.opahypothesis.html b/reference/plot.opahypothesis.html
index e99cef8..0844402 100644
--- a/reference/plot.opahypothesis.html
+++ b/reference/plot.opahypothesis.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/print.opaGroupComparison.html b/reference/print.opaGroupComparison.html
index dedee89..e2eaaa8 100644
--- a/reference/print.opaGroupComparison.html
+++ b/reference/print.opaGroupComparison.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/print.opaHypothesisComparison.html b/reference/print.opaHypothesisComparison.html
index ca819c3..2fe8712 100644
--- a/reference/print.opaHypothesisComparison.html
+++ b/reference/print.opaHypothesisComparison.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/print.opafit.html b/reference/print.opafit.html
index 5092769..1a8756f 100644
--- a/reference/print.opafit.html
+++ b/reference/print.opafit.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
     <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
diff --git a/reference/print.opahypothesis.html b/reference/print.opahypothesis.html
index 3fb1b05..ad2507a 100644
--- a/reference/print.opahypothesis.html
+++ b/reference/print.opahypothesis.html
@@ -10,7 +10,7 @@
     
     <a class="navbar-brand me-2" href="../index.html">opa</a>
 
-    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.025</small>
+    <small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">0.8.1.026</small>
 
     
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diff --git a/reference/summary.opafit.html b/reference/summary.opafit.html
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diff --git a/search.json b/search.json
index 432eb8b..55ba774 100644
--- a/search.json
+++ b/search.json
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-[{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc. <http://fsf.org/> Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. 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Patents","title":"GNU General Public License","text":"“contributor” copyright holder authorizes use License Program work Program based. work thus licensed called contributor’s “contributor version”. contributor’s “essential patent claims” patent claims owned controlled contributor, whether already acquired hereafter acquired, infringed manner, permitted License, making, using, selling contributor version, include claims infringed consequence modification contributor version. purposes definition, “control” includes right grant patent sublicenses manner consistent requirements License. contributor grants non-exclusive, worldwide, royalty-free patent license contributor’s essential patent claims, make, use, sell, offer sale, import otherwise run, modify propagate contents contributor version. following three paragraphs, “patent license” express agreement commitment, however denominated, enforce patent (express permission practice patent covenant sue patent infringement). “grant” patent license party means make agreement commitment enforce patent party. convey covered work, knowingly relying patent license, Corresponding Source work available anyone copy, free charge terms License, publicly available network server readily accessible means, must either (1) cause Corresponding Source available, (2) arrange deprive benefit patent license particular work, (3) arrange, manner consistent requirements License, extend patent license downstream recipients. “Knowingly relying” means actual knowledge , patent license, conveying covered work country, recipient’s use covered work country, infringe one identifiable patents country reason believe valid. , pursuant connection single transaction arrangement, convey, propagate procuring conveyance , covered work, grant patent license parties receiving covered work authorizing use, propagate, modify convey specific copy covered work, patent license grant automatically extended recipients covered work works based . patent license “discriminatory” include within scope coverage, prohibits exercise , conditioned non-exercise one rights specifically granted License. may convey covered work party arrangement third party business distributing software, make payment third party based extent activity conveying work, third party grants, parties receive covered work , discriminatory patent license () connection copies covered work conveyed (copies made copies), (b) primarily connection specific products compilations contain covered work, unless entered arrangement, patent license granted, prior 28 March 2007. Nothing License shall construed excluding limiting implied license defenses infringement may otherwise available applicable patent law.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_12-no-surrender-of-others-freedom","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"12. No Surrender of Others’ Freedom","title":"GNU General Public License","text":"conditions imposed (whether court order, agreement otherwise) contradict conditions License, excuse conditions License. convey covered work satisfy simultaneously obligations License pertinent obligations, consequence may convey . example, agree terms obligate collect royalty conveying convey Program, way satisfy terms License refrain entirely conveying Program.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_13-use-with-the-gnu-affero-general-public-license","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"13. Use with the GNU Affero General Public License","title":"GNU General Public License","text":"Notwithstanding provision License, permission link combine covered work work licensed version 3 GNU Affero General Public License single combined work, convey resulting work. terms License continue apply part covered work, special requirements GNU Affero General Public License, section 13, concerning interaction network apply combination .","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_14-revised-versions-of-this-license","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"14. Revised Versions of this License","title":"GNU General Public License","text":"Free Software Foundation may publish revised /new versions GNU General Public License time time. new versions similar spirit present version, may differ detail address new problems concerns. version given distinguishing version number. Program specifies certain numbered version GNU General Public License “later version” applies , option following terms conditions either numbered version later version published Free Software Foundation. Program specify version number GNU General Public License, may choose version ever published Free Software Foundation. Program specifies proxy can decide future versions GNU General Public License can used, proxy’s public statement acceptance version permanently authorizes choose version Program. Later license versions may give additional different permissions. However, additional obligations imposed author copyright holder result choosing follow later version.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_15-disclaimer-of-warranty","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"15. Disclaimer of Warranty","title":"GNU General Public License","text":"WARRANTY PROGRAM, EXTENT PERMITTED APPLICABLE LAW. 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Limitation of Liability","title":"GNU General Public License","text":"EVENT UNLESS REQUIRED APPLICABLE LAW AGREED WRITING COPYRIGHT HOLDER, PARTY MODIFIES /CONVEYS PROGRAM PERMITTED , LIABLE DAMAGES, INCLUDING GENERAL, SPECIAL, INCIDENTAL CONSEQUENTIAL DAMAGES ARISING USE INABILITY USE PROGRAM (INCLUDING LIMITED LOSS DATA DATA RENDERED INACCURATE LOSSES SUSTAINED THIRD PARTIES FAILURE PROGRAM OPERATE PROGRAMS), EVEN HOLDER PARTY ADVISED POSSIBILITY DAMAGES.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_17-interpretation-of-sections-15-and-16","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"17. Interpretation of Sections 15 and 16","title":"GNU General Public License","text":"disclaimer warranty limitation liability provided given local legal effect according terms, reviewing courts shall apply local law closely approximates absolute waiver civil liability connection Program, unless warranty assumption liability accompanies copy Program return fee. END TERMS CONDITIONS","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"how-to-apply-these-terms-to-your-new-programs","dir":"","previous_headings":"","what":"How to Apply These Terms to Your New Programs","title":"GNU General Public License","text":"develop new program, want greatest possible use public, best way achieve make free software everyone can redistribute change terms. , attach following notices program. safest attach start source file effectively state exclusion warranty; file least “copyright” line pointer full notice found. Also add information contact electronic paper mail. program terminal interaction, make output short notice like starts interactive mode: hypothetical commands show w show c show appropriate parts General Public License. course, program’s commands might different; GUI interface, use “box”. also get employer (work programmer) school, , sign “copyright disclaimer” program, necessary. information , apply follow GNU GPL, see <http://www.gnu.org/licenses/>. GNU General Public License permit incorporating program proprietary programs. program subroutine library, may consider useful permit linking proprietary applications library. want , use GNU Lesser General Public License instead License. first, please read <http://www.gnu.org/philosophy/--lgpl.html>.","code":"<one line to give the program's name and a brief idea of what it does.> Copyright (C) <year>  <name of author>  This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.  This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.  You should have received a copy of the GNU General Public License along with this program.  If not, see <http://www.gnu.org/licenses/>. <program>  Copyright (C) <year>  <name of author> This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"opa","text":"opa implementation methods described publications including Thorngate (1987) Grice et al. (2015). Thorngate (1987) attributes original idea : Parsons, D. (1975). directory tunes musical themes. S. Brown.","code":""},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"how-ordinal-pattern-analysis-works","dir":"Articles","previous_headings":"","what":"How ordinal pattern analysis works","title":"opa","text":"Ordinal pattern analysis simple non-parametric method, similar Kendall’s Tau. Whereas Kendall’s tau measure similarity two data sets terms rank ordering, ordinal pattern analysis intended quantify match hypothesis patterns individual-level data across conditions measurement instances. Ordinal pattern analysis works comparing relative ordering pairs observations computing whether pairwise relations matched hypothesis. pairwise ordered relation classified increase, decrease, change. classifications encoded 1, -1 0, respectively. example, hypothesis monotonic increase response variable across four experimental conditions can specified : Note absolute values important, relative ordering. hypothesis h encodes six pairwise relations, increases: 1 1 1 1 1 1. row individual data representing measurements across four conditions, : encodes six ordered pairwise relations 1 1 1 -1 1 1. percentage orderings correctly classified hypothesis (PCC) main quantity interest ordinal pattern analysis. Comparing h dat, PCC 5/6 = 0.833 83.3%. hypothesis generates greater PCC preferred hypothesis generates lower PCC given data. also possible calculate chance-value PCC equal chance PCC least great PCC observed data occur result random re-ordering data. Chance values can computed using randomization test.","code":"(h <- c(1, 2, 3, 4)) #> [1] 1 2 3 4 dat <- c(65.3, 68.8, 67.0, 73.1)"},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"modeling-repeated-measures-data","dir":"Articles","previous_headings":"","what":"Modeling repeated measures data","title":"opa","text":"installed, can load opa ","code":"library(opa)"},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"data","dir":"Articles","previous_headings":"Modeling repeated measures data","what":"Data","title":"opa","text":"example use sleepstudy data lme4 package.","code":""},{"path":[]},{"path":[]},{"path":[]},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"references","dir":"Articles","previous_headings":"","what":"References","title":"opa","text":"Grice, J. W., Craig, D. P. ., & Abramson, C. . (2015). Simple Transparent Alternative Repeated Measures ANOVA. SAGE Open, 5(3), 215824401560419. https://doi.org/10.1177/2158244015604192 Parsons, D. (1975). directory tunes musical themes. S. Brown. Thorngate, W. (1987). Ordinal Pattern Analysis: Method Assessing Theory-Data Fit. Advances Psychology, 40, 345–364. https://doi.org/10.1016/S0166-4115(08)60083-7","code":""},{"path":"https://timbeechey.github.io/opa/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Timothy Beechey. Author, maintainer.","code":""},{"path":"https://timbeechey.github.io/opa/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Beechey T (2024). opa: Implementation Ordinal Pattern Analysis. R package version 0.8.1.025, https://timbeechey.github.io/opa/.","code":"@Manual{,   title = {opa: An Implementation of Ordinal Pattern Analysis},   author = {Timothy Beechey},   year = {2024},   note = {R package version 0.8.1.025},   url = {https://timbeechey.github.io/opa/}, }"},{"path":"https://timbeechey.github.io/opa/index.html","id":"opa-","dir":"","previous_headings":"","what":"An Implementation of Ordinal Pattern Analysis","title":"An Implementation of Ordinal Pattern Analysis","text":"R package ordinal pattern analysis.","code":""},{"path":"https://timbeechey.github.io/opa/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"An Implementation of Ordinal Pattern Analysis","text":"opa can installed CRAN : can install development version opa GitHub :","code":"install.packages(\"opa\") # install.packages(\"remotes\") remotes::install_github(\"timbeechey/opa\")"},{"path":"https://timbeechey.github.io/opa/index.html","id":"using-opa","dir":"","previous_headings":"","what":"Using opa","title":"An Implementation of Ordinal Pattern Analysis","text":"hypothesized relative ordering response variable across conditions specified numeric vector: hypothesis can visualised plot() function:  Data wide format one column per measurement condition one row per individual: ordinal pattern analysis model hypothesis h matches individual pattern results dat can fitted using: summary model output can viewed using: Individual-level model output can plotted using:  aid interpretation, individual PCCs c-values can also plotted relative user-specified thresholds:","code":"library(opa) (h <- hypothesis(c(1, 2, 4, 3), type = \"pairwise\")) #> ********** Ordinal Hypothesis ********** #> Hypothesis type: pairwise  #> Raw hypothesis: #>  1 2 4 3  #> Ordinal relations: #>  1 1 1 1 1 -1  #> N conditions: 4  #> N hypothesised ordinal relations: 6  #> N hypothesised increases: 5  #> N hypothesised decreases: 1  #> N hypothesised equalities: 0 plot(h) set.seed(123)  dat <- data.frame(t1 = rnorm(20, mean = 12, sd = 2),                   t2 = rnorm(20, mean = 15, sd = 2),                   t3 = rnorm(20, mean = 20, sd = 2),                   t4 = rnorm(20, mean = 17, sd = 2))                    round(dat, 2) #>       t1    t2    t3    t4 #> 1  10.88 12.86 18.61 17.76 #> 2  11.54 14.56 19.58 16.00 #> 3  15.12 12.95 17.47 16.33 #> 4  12.14 13.54 24.34 14.96 #> 5  12.26 13.75 22.42 14.86 #> 6  15.43 11.63 17.75 17.61 #> 7  12.92 16.68 19.19 17.90 #> 8   9.47 15.31 19.07 17.11 #> 9  10.63 12.72 21.56 18.84 #> 10 11.11 17.51 19.83 21.10 #> 11 14.45 15.85 20.51 16.02 #> 12 12.72 14.41 19.94 12.38 #> 13 12.80 16.79 19.91 19.01 #> 14 12.22 16.76 22.74 15.58 #> 15 10.89 16.64 19.55 15.62 #> 16 15.57 16.38 23.03 19.05 #> 17 13.00 16.11 16.90 16.43 #> 18  8.07 14.88 21.17 14.56 #> 19 13.40 14.39 20.25 17.36 #> 20 11.05 14.24 20.43 16.72 opamod <- opa(dat, h) summary(opamod) #> Ordinal Pattern Analysis of 4 observations for 20 individuals in 1 group  #>  #> Between subjects results: #>          PCC cval #> pooled 93.33    0 #>  #> Within subjects results: #>       PCC cval #> 1  100.00 0.04 #> 2  100.00 0.04 #> 3   83.33 0.17 #> 4  100.00 0.05 #> 5  100.00 0.04 #> 6   83.33 0.18 #> 7  100.00 0.04 #> 8  100.00 0.04 #> 9  100.00 0.04 #> 10  83.33 0.15 #> 11 100.00 0.04 #> 12  66.67 0.38 #> 13 100.00 0.04 #> 14  83.33 0.16 #> 15  83.33 0.18 #> 16 100.00 0.04 #> 17 100.00 0.05 #> 18  83.33 0.17 #> 19 100.00 0.04 #> 20 100.00 0.04 #>  #> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0. #> Chance-values were calculated from 1000 random orderings. plot(opamod) plot(opamod, pcc_threshold = 90, cval_threshold = 0.1)"},{"path":"https://timbeechey.github.io/opa/index.html","id":"pairwise-comparison-of-measurement-conditions","dir":"","previous_headings":"Using opa","what":"Pairwise comparison of measurement conditions","title":"An Implementation of Ordinal Pattern Analysis","text":"Pairwise comparisons measurement conditions can calculated applying compare_conditions() function opafit object produced call opa():","code":"condition_comparisons <- compare_conditions(opamod)  print(condition_comparisons) #> Pairwise PCCs: #>     1   2  3 4 #> 1   -   -  - - #> 2  90   -  - - #> 3 100 100  - - #> 4  95  80 95 - #>  #> Pairwise chance values: #>        1      2      3 4 #> 1      -      -      - - #> 2 <0.001      -      - - #> 3 <0.001 <0.001      - - #> 4 <0.001  0.002 <0.001 -"},{"path":"https://timbeechey.github.io/opa/index.html","id":"multiple-groups","dir":"","previous_headings":"Using opa","what":"Multiple groups","title":"An Implementation of Ordinal Pattern Analysis","text":"data consist multiple groups categorical grouping variable can passed group keyword produce results group within data, addition individual results. summary output displays results organised group. Similarly, plotting output shows individual PCCs c-values group.","code":"dat$group <- rep(c(\"A\", \"B\", \"C\", \"D\"), 5) dat$group <- factor(dat$group, levels = c(\"A\", \"B\", \"C\", \"D\"))  opamod2 <- opa(dat[, 1:4], h, group = dat$group) summary(opamod2, digits = 3) #> Ordinal Pattern Analysis of 4 observations for 20 individuals in 4 groups  #>  #> Between subjects results: #>       PCC cval #> A 100.000    0 #> B  86.667    0 #> C  93.333    0 #> D  93.333    0 #>  #> Within subjects results: #>   Individual     PCC  cval #> A          1 100.000 0.034 #> A          5 100.000 0.035 #> A          9 100.000 0.045 #> A         13 100.000 0.044 #> A         17 100.000 0.047 #> B          2 100.000 0.053 #> B          6  83.333 0.191 #> B         10  83.333 0.165 #> B         14  83.333 0.166 #> B         18  83.333 0.159 #> C          3  83.333 0.185 #> C          7 100.000 0.044 #> C         11 100.000 0.043 #> C         15  83.333 0.158 #> C         19 100.000 0.050 #> D          4 100.000 0.055 #> D          8 100.000 0.047 #> D         12  66.667 0.379 #> D         16 100.000 0.050 #> D         20 100.000 0.044 #>  #> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0. #> Chance-values were calculated from 1000 random orderings. plot(opamod2)"},{"path":"https://timbeechey.github.io/opa/index.html","id":"comparing-fit-by-group","dir":"","previous_headings":"Using opa","what":"Comparing fit by group","title":"An Implementation of Ordinal Pattern Analysis","text":"chance-value difference group-level PCCs two groups can calculated using compare_groups() function. difference group-level PCCs along c-value difference can checked:","code":"group_comp <- compare_groups(opamod2, \"A\", \"B\") summary(group_comp) #> ********* Group Comparison ********** #> Group 1: A  #> Group 2: B  #> Group 1 PCC: 100  #> Group 2 PCC: 86.66667  #> PCC difference: 13.33333  #> cval: 0.43"},{"path":"https://timbeechey.github.io/opa/index.html","id":"acknowledgements","dir":"","previous_headings":"","what":"Acknowledgements","title":"An Implementation of Ordinal Pattern Analysis","text":"Development opa supported Medical Research Foundation Fellowship (MRF-049-0004-F-BEEC-C0899).","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"Calculates PCCs c-values based pairwise comparison conditions.","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"","code":"compare_conditions(result, nreps = 1000L)"},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"result object class \"opafit\" produced call opa(). nreps integer","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"compare_conditions returns list following elements pcc_mat lower triangle matrix containing PCCs calculated   pairing data columns. cval_mat lower triangle matrix containing c-values calculated   pairing data columns. pccs vector containing PCCs calculated pairing data. cvals vector containing c-values calculated pairing data. nreps number permutations used calculate c-values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11),                   t4 = c(10, 5, 11, 12)) opamod <- opa(dat, 1:4) compare_conditions(opamod) #> Pairwise PCCs: #>     1  2  3 4 #> 1   -  -  - - #> 2  50  -  - - #> 3  75 25  - - #> 4 100 50 75 - #>  #> Pairwise chance values: #>       1     2    3 4 #> 1     -     -    - - #> 2 0.497     -    - - #> 3 0.318 0.898    - - #> 4 0.052 0.696 0.13 -"},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"Calculate c-value difference PCCs produced two groups","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"","code":"compare_groups(m, group1, group2)"},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"m object class \"opafit\" produced call opa(). group1 character string matches group level passed opa(). group2 character string matches group level passed opa().","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"object class \"opaGroupComparison\".","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"","code":"dat <- data.frame(group = c(\"a\", \"b\", \"a\", \"b\"),                   t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) dat$group <- factor(dat$group, levels = c(\"a\", \"b\")) opamod <- opa(dat[,2:4], 1:3, group = dat$group) compare_groups(opamod, \"a\", \"b\") #> ********* Group Comparison ********** #> Group 1: a  #> Group 2: b  #> Group 1 PCC: 33.33333  #> Group 2 PCC: 66.66667  #> PCC difference: 33.33333  #> cval: 0.42"},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"Calculate c-value difference PCCs produced two hypotheses","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"","code":"compare_hypotheses(m1, m2)"},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"m1 object class \"opafit\" produced call opa(). m2 object class \"opafit\" produced call opa().","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"object class \"opaHypothesisComparison\".","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11),                   t4 = c(10, 5, 11, 12)) opamod1 <- opa(dat, c(1, 2, 3, 4)) opamod2 <- opa(dat, c(1, 4, 2, 3)) compare_hypotheses(opamod1, opamod2) #> ********* Hypothesis Comparison ********** #> H1: 1 2 3 4  #> H2: 1 4 2 3  #> H1 PCC: 62.5  #> H2 PCC: 66.66667  #> PCC difference: 4.166667  #> cval: 0.895"},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"Return number pairs observations matched hypothesis","code":""},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"","code":"correct_pairs(m)"},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"non-negative integer","code":""},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) correct_pairs(opamod) #> [1] 6"},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot individual chance values — cval_plot","title":"Plot individual chance values — cval_plot","text":"Plot individual chance values","code":""},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot individual chance values — cval_plot","text":"","code":"cval_plot(m, threshold = NULL, title = TRUE, legend = TRUE)"},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot individual chance values — cval_plot","text":"m object class \"opafit\" threshold boolean indicating whether plot threshold abline title boolean indicating whether include plot title legend boolean indicating whether include legend n groups > 1","code":""},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot individual chance values — cval_plot","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot individual chance values — cval_plot","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) cval_plot(opamod)  cval_plot(opamod, threshold = 0.1)"},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the group chance values of the specified model — group_cvals","title":"Return the group chance values of the specified model — group_cvals","text":"Return group chance values specified model","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the group chance values of the specified model — group_cvals","text":"","code":"group_cvals(m)"},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the group chance values of the specified model — group_cvals","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the group chance values of the specified model — group_cvals","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the group chance values of the specified model — group_cvals","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) group_cvals(opamod) #> [1] 0.241"},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the group PCCs of the specified model — group_pccs","title":"Return the group PCCs of the specified model — group_pccs","text":"Return group PCCs specified model","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the group PCCs of the specified model — group_pccs","text":"","code":"group_pccs(m)"},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the group PCCs of the specified model — group_pccs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the group PCCs of the specified model — group_pccs","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the group PCCs of the specified model — group_pccs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) group_pccs(opamod) #> [1] 50"},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Group-level PCC and chance values. — group_results","title":"Group-level PCC and chance values. — group_results","text":"Group-level PCC chance values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Group-level PCC and chance values. — group_results","text":"","code":"group_results(m, digits)"},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Group-level PCC and chance values. — group_results","text":"m object class \"opafit\" produced opa(). digits positive integer.","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Group-level PCC and chance values. — group_results","text":"matrix 1 row per group.","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Group-level PCC and chance values. — group_results","text":"model fitted grouping variable, single PCC c-value returned. grouping variable specified call opa PCCs c-values returned factor level grouping variable.","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Group-level PCC and chance values. — group_results","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) group_results(opamod) #>        PCC  cval #> pooled  50 0.247"},{"path":"https://timbeechey.github.io/opa/reference/hypothesis.html","id":null,"dir":"Reference","previous_headings":"","what":"create a hypothesis object — hypothesis","title":"create a hypothesis object — hypothesis","text":"create hypothesis object","code":""},{"path":"https://timbeechey.github.io/opa/reference/hypothesis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"create a hypothesis object — hypothesis","text":"","code":"hypothesis(xs, type = \"pairwise\")"},{"path":"https://timbeechey.github.io/opa/reference/hypothesis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"create a hypothesis object — hypothesis","text":"xs numeric vector type string","code":""},{"path":"https://timbeechey.github.io/opa/reference/hypothesis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"create a hypothesis object — hypothesis","text":"list containing following elements","code":""},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"Return number pairs observations matched hypothesis","code":""},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"","code":"incorrect_pairs(m)"},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"non-negative integer","code":""},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) incorrect_pairs(opamod) #> [1] 6"},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the individual chance values of the specified model — individual_cvals","title":"Return the individual chance values of the specified model — individual_cvals","text":"Return individual chance values specified model","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the individual chance values of the specified model — individual_cvals","text":"","code":"individual_cvals(m)"},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the individual chance values of the specified model — individual_cvals","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the individual chance values of the specified model — individual_cvals","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the individual chance values of the specified model — individual_cvals","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) individual_cvals(opamod) #> [1] 1.000 0.512 0.480 0.318"},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the individual PCCs of the specified model — individual_pccs","title":"Return the individual PCCs of the specified model — individual_pccs","text":"Return individual PCCs specified model","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the individual PCCs of the specified model — individual_pccs","text":"","code":"individual_pccs(m)"},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the individual PCCs of the specified model — individual_pccs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the individual PCCs of the specified model — individual_pccs","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the individual PCCs of the specified model — individual_pccs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) individual_pccs(opamod) #> [1]  0.00000 66.66667 66.66667 66.66667"},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Individual-level PCC and chance values. — individual_results","title":"Individual-level PCC and chance values. — individual_results","text":"Individual-level PCC chance values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Individual-level PCC and chance values. — individual_results","text":"","code":"individual_results(m, digits)"},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Individual-level PCC and chance values. — individual_results","text":"m object class \"opafit\" produced opa() digits integer","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Individual-level PCC and chance values. — individual_results","text":"matrix containing column PCC values column c-values 1 row per row data.","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Individual-level PCC and chance values. — individual_results","text":"opa model fitted grouping variable, matrix PCCs c-values returned corresponding order rows data. opa model fitted grouping variable specified, table PCCs c-values returned ordered factor level grouping variable.","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Individual-level PCC and chance values. — individual_results","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) individual_results(opamod) #>     PCC cval #> 1  0.00 1.00 #> 2 66.67 0.52 #> 3 66.67 0.55 #> 4 66.67 0.35"},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":null,"dir":"Reference","previous_headings":"","what":"Fit an ordinal pattern analysis model — opa","title":"Fit an ordinal pattern analysis model — opa","text":"opa used fit ordinal pattern analysis models computing percentage pair orderings row data matched corresponding pair orderings hypothesis, addition chance permutation data producing percentage match great.","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fit an ordinal pattern analysis model — opa","text":"","code":"opa(   dat,   hypothesis,   group = NULL,   pairing_type = \"pairwise\",   diff_threshold = 0,   nreps = 1000L )"},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fit an ordinal pattern analysis model — opa","text":"dat data frame hypothesis numeric vector group optional factor vector pairing_type string diff_threshold positive integer floating point number nreps integer, ignored cval_method = \"exact\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fit an ordinal pattern analysis model — opa","text":"opa returns object class \"opafit\". object class \"opafit\" list containing folllowing components: group_pcc percentage pairwise orderings pooled data   rows correctly classified hypothesis. individual_pccs vector containing percentage pairwise   orderings correctly classified hypothesis data   row. correct_pairs integer representing number pairwise   orderings pooled across data rows correctly classified   hypothesis. total_pairs integer, number pair orderings contained   data. group_cval group-level chance value. individual_cvals vector containing chance values data   row rand_pccs vector PCCS calculated random ordering   length equal nreps, list vectors group vector   passed opa(). call matched call hypothesis hypothesis vector passed opa() pairing_type string indicating method pairing passed   opa(). diff_threshold numeric difference threshold used calculate   PCCs. value passed diff_threshold, default   0 used. data data.frame passed opa(). groups vector groups passed opa. group vector   passed opa() default NULL used. nreps integer, number random re-orderings data   used compute chance values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fit an ordinal pattern analysis model — opa","text":"Data expected wide format 1 row per individual 1 column per measurement condition. Data must contain columns consisting numerical values dependent variable. length hypothesis must equal number columns dependent variable data.frame dat. independent variable must passed separately vector group keyword. grouping vector must factor. pairing_type must either \"pairwise\" \"adjacent\". \"pairwise\" option considered relative ordering every pair observations data every pair elements hypothesis. \"adjacent\" option considers ordering adjacent pairs . unspecified, default \"pairwise\". diff_threshold may positive integer double. unspecified default zero threshold used. diff_threshold never applied hypothesis. nreps specifies number random reorderigs use calculation chance-values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Fit an ordinal pattern analysis model — opa","text":"Grice, J. W., Craig, D. P. ., & Abramson, C. . (2015). Simple Transparent Alternative Repeated Measures ANOVA. SAGE Open, 5(3), 215824401560419. <https://doi.org/10.1177/2158244015604192> Thorngate, W. (1987). Ordinal Pattern Analysis: Method Assessing Theory-Data Fit. Advances Psychology, 40, 345–364. <https://doi.org/10.1016/S0166-4115(08)60083-7>","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fit an ordinal pattern analysis model — opa","text":"","code":"dat <- data.frame(group = c(\"a\", \"b\", \"a\", \"b\"),                   t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) dat$group <- factor(dat$group, levels = c(\"a\", \"b\")) opamod <- opa(dat[,2:4], 1:3) opa(dat[,2:4], 1:3) #> opa(dat = dat[, 2:4], hypothesis = 1:3) opa(dat[,2:4], 1:3, nreps = 500) #> opa(dat = dat[, 2:4], hypothesis = 1:3, nreps = 500) opa(dat[,2:4], 1:3, pairing_type = \"adjacent\") #> opa(dat = dat[, 2:4], hypothesis = 1:3, pairing_type = \"adjacent\") opa(dat[,2:4], 1:3, diff_threshold = 1) #> opa(dat = dat[, 2:4], hypothesis = 1:3, diff_threshold = 1) opa(dat[,2:4], 1:3, group = dat$group) #> opa(dat = dat[, 2:4], hypothesis = 1:3, group = dat$group)"},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot individual PCCs. — pcc_plot","title":"Plot individual PCCs. — pcc_plot","text":"Plot individual PCCs.","code":""},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot individual PCCs. — pcc_plot","text":"","code":"pcc_plot(m, threshold = NULL, title = TRUE, legend = TRUE)"},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot individual PCCs. — pcc_plot","text":"m object class \"opafit\" threshold boolean indicating whether plot threshold abline title boolean indicating whether include plot title legend boolean indicating whether include legend","code":""},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot individual PCCs. — pcc_plot","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot individual PCCs. — pcc_plot","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) pcc_plot(opamod)  pcc_plot(opamod, threshold = 85)"},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots individual-level PCCs and chance-values. — plot.opafit","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"Plots individual-level PCCs chance-values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"","code":"# S3 method for opafit plot(x, pcc_threshold = NULL, cval_threshold = NULL, ...)"},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"x object class \"opafit\" produced opa() pcc_threshold number used x-intercept plot PCC threshold abline cval_threshold number used x-intercept plot c-value threshold abline ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) plot(opamod)"},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a hypothesis. — plot.opahypothesis","title":"Plot a hypothesis. — plot.opahypothesis","text":"Plot hypothesis.","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a hypothesis. — plot.opahypothesis","text":"","code":"# S3 method for opahypothesis plot(x, title = TRUE, ...)"},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a hypothesis. — plot.opahypothesis","text":"x object class \"opaHypothesis\" title boolean indicating whether include plot title ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a hypothesis. — plot.opahypothesis","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a hypothesis. — plot.opahypothesis","text":"","code":"h <- hypothesis(c(1,2,3,3,3)) plot(h)"},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"Prints summary results hypothesis comparison.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"","code":"# S3 method for opaGroupComparison print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"x object class \"opaHypothesisComparison\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"","code":"dat <- data.frame(group = c(\"a\", \"b\", \"a\", \"b\"),                   t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) dat$group <- factor(dat$group, levels = c(\"a\", \"b\")) opamod <- opa(dat[,2:4], 1:3, group = dat$group) z <- compare_groups(opamod, \"a\", \"b\") print(z) #> ********* Group Comparison ********** #> Group 1: a  #> Group 2: b  #> Group 1 PCC: 33.33333  #> Group 2 PCC: 66.66667  #> PCC difference: 33.33333  #> cval: 0.371"},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"Prints summary results hypothesis comparison.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"","code":"# S3 method for opaHypothesisComparison print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"x object class \"opaHypothesisComparison\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11),                   t4 = c(10, 5, 11, 12)) opamod1 <- opa(dat, c(1, 2, 3, 4)) opamod2 <- opa(dat, c(1, 4, 2, 3)) z <- compare_hypotheses(opamod1, opamod2) print(z) #> ********* Hypothesis Comparison ********** #> H1: 1 2 3 4  #> H2: 1 4 2 3  #> H1 PCC: 62.5  #> H2 PCC: 66.66667  #> PCC difference: 4.166667  #> cval: 0.886"},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":null,"dir":"Reference","previous_headings":"","what":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"Displays call used fit ordinal pattern analysis model.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"","code":"# S3 method for opafit print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"x object class \"opafit\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) print(opamod) #> opa(dat = dat, hypothesis = 1:3)"},{"path":"https://timbeechey.github.io/opa/reference/print.opahypothesis.html","id":null,"dir":"Reference","previous_headings":"","what":"Print details of a hypothesis — print.opahypothesis","title":"Print details of a hypothesis — print.opahypothesis","text":"Print details hypothesis","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opahypothesis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print details of a hypothesis — print.opahypothesis","text":"","code":"# S3 method for opahypothesis print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.opahypothesis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print details of a hypothesis — print.opahypothesis","text":"x object type \"opaHypothesis\" ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opahypothesis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print details of a hypothesis — print.opahypothesis","text":"return value, called side-effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":null,"dir":"Reference","previous_headings":"","what":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"Displays results pairwise ordinal pattern analysis.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"","code":"# S3 method for pairwiseopafit print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"x object class \"pairwiseopafit\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) pw <- compare_conditions(opamod) print(pw) #> Pairwise PCCs: #>    1  2 3 #> 1  -  - - #> 2 50  - - #> 3 75 25 - #>  #> Pairwise chance values: #>       1     2 3 #> 1     -     - - #> 2 0.516     - - #> 3 0.318 0.878 - print(pw, digits = 2) #> Pairwise PCCs: #>    1  2 3 #> 1  -  - - #> 2 50  - - #> 3 75 25 - #>  #> Pairwise chance values: #>       1     2 3 #> 1     -     - - #> 2 0.516     - - #> 3 0.318 0.878 -"},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"Return random order generated PCCs used calculate group chance value","code":""},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"","code":"random_pccs(m)"},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) random_pccs(opamod) #>              [,1] #>    [1,] 50.000000 #>    [2,] 50.000000 #>    [3,] 25.000000 #>    [4,] 25.000000 #>    [5,] 41.666667 #>    [6,] 33.333333 #>    [7,] 41.666667 #>    [8,] 33.333333 #>    [9,] 58.333333 #>   [10,] 41.666667 #>   [11,] 41.666667 #>   [12,]  8.333333 #>   [13,] 58.333333 #>   [14,] 58.333333 #>   [15,] 41.666667 #>   [16,] 33.333333 #>   [17,] 58.333333 #>   [18,]  8.333333 #>   [19,] 25.000000 #>   [20,] 66.666667 #>   [21,] 25.000000 #>   [22,] 50.000000 #>   [23,] 25.000000 #>   [24,] 41.666667 #>   [25,] 25.000000 #>   [26,] 33.333333 #>   [27,] 50.000000 #>   [28,] 41.666667 #>   [29,] 41.666667 #>   [30,] 41.666667 #>   [31,]  8.333333 #>   [32,] 41.666667 #>   [33,] 58.333333 #>   [34,] 50.000000 #>   [35,] 33.333333 #>   [36,] 50.000000 #>   [37,] 33.333333 #>   [38,] 66.666667 #>   [39,] 41.666667 #>   [40,] 41.666667 #>   [41,] 50.000000 #>   [42,] 41.666667 #>   [43,] 50.000000 #>   [44,] 33.333333 #>   [45,] 33.333333 #>   [46,] 16.666667 #>   [47,] 50.000000 #>   [48,] 16.666667 #>   [49,] 25.000000 #>   [50,] 58.333333 #>   [51,] 25.000000 #>   [52,] 33.333333 #>   [53,] 41.666667 #>   [54,] 33.333333 #>   [55,] 66.666667 #>   [56,] 25.000000 #>   [57,] 41.666667 #>   [58,] 41.666667 #>   [59,] 33.333333 #>   [60,] 25.000000 #>   [61,] 33.333333 #>   [62,] 33.333333 #>   [63,] 25.000000 #>   [64,] 41.666667 #>   [65,] 41.666667 #>   [66,]  0.000000 #>   [67,] 25.000000 #>   [68,] 66.666667 #>   [69,] 25.000000 #>   [70,] 41.666667 #>   [71,] 33.333333 #>   [72,] 33.333333 #>   [73,] 25.000000 #>   [74,] 41.666667 #>   [75,] 41.666667 #>   [76,] 50.000000 #>   [77,] 50.000000 #>   [78,] 33.333333 #>   [79,] 33.333333 #>   [80,] 33.333333 #>   [81,] 66.666667 #>   [82,] 50.000000 #>   [83,] 58.333333 #>   [84,] 33.333333 #>   [85,] 50.000000 #>   [86,] 33.333333 #>   [87,] 33.333333 #>   [88,] 41.666667 #>   [89,] 33.333333 #>   [90,] 16.666667 #>   [91,] 25.000000 #>   [92,] 58.333333 #>   [93,] 50.000000 #>   [94,] 25.000000 #>   [95,] 41.666667 #>   [96,] 41.666667 #>   [97,] 16.666667 #>   [98,] 50.000000 #>   [99,] 50.000000 #>  [100,] 33.333333 #>  [101,] 58.333333 #>  [102,] 33.333333 #>  [103,] 33.333333 #>  [104,] 33.333333 #>  [105,] 41.666667 #>  [106,] 50.000000 #>  [107,] 50.000000 #>  [108,] 50.000000 #>  [109,] 33.333333 #>  [110,] 41.666667 #>  [111,]  8.333333 #>  [112,] 66.666667 #>  [113,] 33.333333 #>  [114,] 58.333333 #>  [115,] 75.000000 #>  [116,] 41.666667 #>  [117,] 33.333333 #>  [118,] 66.666667 #>  [119,] 41.666667 #>  [120,] 16.666667 #>  [121,] 50.000000 #>  [122,] 41.666667 #>  [123,] 58.333333 #>  [124,] 50.000000 #>  [125,] 41.666667 #>  [126,] 25.000000 #>  [127,] 50.000000 #>  [128,] 33.333333 #>  [129,] 33.333333 #>  [130,] 41.666667 #>  [131,] 41.666667 #>  [132,] 16.666667 #>  [133,] 66.666667 #>  [134,] 41.666667 #>  [135,] 25.000000 #>  [136,] 41.666667 #>  [137,] 33.333333 #>  [138,] 41.666667 #>  [139,] 33.333333 #>  [140,] 58.333333 #>  [141,] 58.333333 #>  [142,] 33.333333 #>  [143,] 50.000000 #>  [144,] 33.333333 #>  [145,] 33.333333 #>  [146,] 50.000000 #>  [147,] 58.333333 #>  [148,] 50.000000 #>  [149,] 50.000000 #>  [150,] 50.000000 #>  [151,] 25.000000 #>  [152,] 41.666667 #>  [153,] 16.666667 #>  [154,] 16.666667 #>  [155,] 25.000000 #>  [156,] 16.666667 #>  [157,] 16.666667 #>  [158,] 25.000000 #>  [159,] 33.333333 #>  [160,] 33.333333 #>  [161,] 41.666667 #>  [162,] 25.000000 #>  [163,] 33.333333 #>  [164,] 33.333333 #>  [165,]  8.333333 #>  [166,] 41.666667 #>  [167,] 75.000000 #>  [168,] 41.666667 #>  [169,] 50.000000 #>  [170,] 41.666667 #>  [171,] 25.000000 #>  [172,] 50.000000 #>  [173,] 33.333333 #>  [174,] 41.666667 #>  [175,] 25.000000 #>  [176,] 41.666667 #>  [177,] 58.333333 #>  [178,] 25.000000 #>  [179,] 33.333333 #>  [180,] 33.333333 #>  [181,] 58.333333 #>  [182,] 33.333333 #>  [183,] 50.000000 #>  [184,]  8.333333 #>  [185,] 50.000000 #>  [186,] 41.666667 #>  [187,] 33.333333 #>  [188,] 50.000000 #>  [189,] 50.000000 #>  [190,] 66.666667 #>  [191,] 25.000000 #>  [192,] 66.666667 #>  [193,] 25.000000 #>  [194,] 25.000000 #>  [195,] 16.666667 #>  [196,] 83.333333 #>  [197,] 41.666667 #>  [198,] 50.000000 #>  [199,] 50.000000 #>  [200,] 41.666667 #>  [201,]  8.333333 #>  [202,] 33.333333 #>  [203,] 50.000000 #>  [204,] 16.666667 #>  [205,] 25.000000 #>  [206,] 41.666667 #>  [207,] 58.333333 #>  [208,] 41.666667 #>  [209,] 50.000000 #>  [210,] 33.333333 #>  [211,] 33.333333 #>  [212,] 66.666667 #>  [213,] 50.000000 #>  [214,] 58.333333 #>  [215,] 41.666667 #>  [216,] 50.000000 #>  [217,] 33.333333 #>  [218,] 50.000000 #>  [219,] 58.333333 #>  [220,] 25.000000 #>  [221,] 25.000000 #>  [222,] 33.333333 #>  [223,] 41.666667 #>  [224,] 41.666667 #>  [225,] 50.000000 #>  [226,] 33.333333 #>  [227,] 58.333333 #>  [228,] 25.000000 #>  [229,] 41.666667 #>  [230,] 50.000000 #>  [231,] 58.333333 #>  [232,] 16.666667 #>  [233,] 58.333333 #>  [234,] 33.333333 #>  [235,] 33.333333 #>  [236,] 33.333333 #>  [237,] 33.333333 #>  [238,] 66.666667 #>  [239,] 58.333333 #>  [240,] 50.000000 #>  [241,] 25.000000 #>  [242,] 50.000000 #>  [243,] 33.333333 #>  [244,] 41.666667 #>  [245,] 50.000000 #>  [246,] 25.000000 #>  [247,] 58.333333 #>  [248,] 58.333333 #>  [249,] 41.666667 #>  [250,] 50.000000 #>  [251,] 66.666667 #>  [252,] 50.000000 #>  [253,] 41.666667 #>  [254,] 41.666667 #>  [255,]  8.333333 #>  [256,] 25.000000 #>  [257,] 41.666667 #>  [258,] 25.000000 #>  [259,] 33.333333 #>  [260,] 50.000000 #>  [261,] 33.333333 #>  [262,] 50.000000 #>  [263,] 16.666667 #>  [264,] 50.000000 #>  [265,] 66.666667 #>  [266,] 58.333333 #>  [267,] 25.000000 #>  [268,] 33.333333 #>  [269,] 58.333333 #>  [270,] 33.333333 #>  [271,] 41.666667 #>  [272,] 50.000000 #>  [273,] 41.666667 #>  [274,] 33.333333 #>  [275,] 50.000000 #>  [276,] 41.666667 #>  [277,] 58.333333 #>  [278,] 58.333333 #>  [279,] 41.666667 #>  [280,] 41.666667 #>  [281,] 33.333333 #>  [282,] 33.333333 #>  [283,] 58.333333 #>  [284,] 41.666667 #>  [285,] 33.333333 #>  [286,] 66.666667 #>  [287,] 25.000000 #>  [288,] 41.666667 #>  [289,] 33.333333 #>  [290,] 25.000000 #>  [291,] 33.333333 #>  [292,] 33.333333 #>  [293,] 16.666667 #>  [294,] 50.000000 #>  [295,] 41.666667 #>  [296,] 50.000000 #>  [297,] 66.666667 #>  [298,] 33.333333 #>  [299,] 66.666667 #>  [300,] 25.000000 #>  [301,] 58.333333 #>  [302,] 58.333333 #>  [303,] 50.000000 #>  [304,] 25.000000 #>  [305,] 41.666667 #>  [306,] 41.666667 #>  [307,] 33.333333 #>  [308,] 41.666667 #>  [309,] 50.000000 #>  [310,] 58.333333 #>  [311,] 16.666667 #>  [312,] 33.333333 #>  [313,] 50.000000 #>  [314,] 33.333333 #>  [315,] 58.333333 #>  [316,] 75.000000 #>  [317,] 25.000000 #>  [318,] 25.000000 #>  [319,] 58.333333 #>  [320,] 50.000000 #>  [321,] 58.333333 #>  [322,] 66.666667 #>  [323,] 41.666667 #>  [324,] 41.666667 #>  [325,] 41.666667 #>  [326,] 66.666667 #>  [327,] 66.666667 #>  [328,] 41.666667 #>  [329,] 25.000000 #>  [330,] 33.333333 #>  [331,] 41.666667 #>  [332,] 41.666667 #>  [333,] 58.333333 #>  [334,] 16.666667 #>  [335,] 16.666667 #>  [336,] 50.000000 #>  [337,] 25.000000 #>  [338,] 66.666667 #>  [339,] 58.333333 #>  [340,] 66.666667 #>  [341,] 16.666667 #>  [342,] 16.666667 #>  [343,] 58.333333 #>  [344,] 58.333333 #>  [345,] 58.333333 #>  [346,] 33.333333 #>  [347,] 50.000000 #>  [348,] 66.666667 #>  [349,] 25.000000 #>  [350,] 50.000000 #>  [351,] 58.333333 #>  [352,] 25.000000 #>  [353,] 33.333333 #>  [354,] 41.666667 #>  [355,] 50.000000 #>  [356,] 41.666667 #>  [357,] 50.000000 #>  [358,] 50.000000 #>  [359,] 75.000000 #>  [360,] 33.333333 #>  [361,] 25.000000 #>  [362,] 41.666667 #>  [363,] 41.666667 #>  [364,] 41.666667 #>  [365,] 41.666667 #>  [366,] 33.333333 #>  [367,] 58.333333 #>  [368,] 25.000000 #>  [369,] 50.000000 #>  [370,] 66.666667 #>  [371,] 58.333333 #>  [372,] 41.666667 #>  [373,] 41.666667 #>  [374,] 50.000000 #>  [375,] 33.333333 #>  [376,] 58.333333 #>  [377,] 58.333333 #>  [378,] 41.666667 #>  [379,] 58.333333 #>  [380,] 75.000000 #>  [381,] 50.000000 #>  [382,] 16.666667 #>  [383,] 41.666667 #>  [384,] 25.000000 #>  [385,] 66.666667 #>  [386,] 41.666667 #>  [387,] 25.000000 #>  [388,] 33.333333 #>  [389,] 50.000000 #>  [390,] 25.000000 #>  [391,] 33.333333 #>  [392,] 50.000000 #>  [393,] 33.333333 #>  [394,] 41.666667 #>  [395,] 41.666667 #>  [396,] 41.666667 #>  [397,] 41.666667 #>  [398,] 41.666667 #>  [399,] 58.333333 #>  [400,] 33.333333 #>  [401,] 33.333333 #>  [402,] 33.333333 #>  [403,] 50.000000 #>  [404,] 41.666667 #>  [405,] 41.666667 #>  [406,] 50.000000 #>  [407,] 50.000000 #>  [408,] 58.333333 #>  [409,] 83.333333 #>  [410,] 66.666667 #>  [411,] 58.333333 #>  [412,] 50.000000 #>  [413,] 50.000000 #>  [414,] 58.333333 #>  [415,] 33.333333 #>  [416,] 58.333333 #>  [417,] 16.666667 #>  [418,] 58.333333 #>  [419,] 33.333333 #>  [420,] 41.666667 #>  [421,] 50.000000 #>  [422,] 16.666667 #>  [423,] 41.666667 #>  [424,] 25.000000 #>  [425,] 58.333333 #>  [426,] 50.000000 #>  [427,] 33.333333 #>  [428,] 33.333333 #>  [429,] 58.333333 #>  [430,] 58.333333 #>  [431,] 33.333333 #>  [432,] 33.333333 #>  [433,] 25.000000 #>  [434,] 41.666667 #>  [435,] 58.333333 #>  [436,] 33.333333 #>  [437,] 41.666667 #>  [438,] 41.666667 #>  [439,] 33.333333 #>  [440,] 16.666667 #>  [441,] 50.000000 #>  [442,] 41.666667 #>  [443,] 41.666667 #>  [444,] 25.000000 #>  [445,] 58.333333 #>  [446,] 25.000000 #>  [447,] 41.666667 #>  [448,] 33.333333 #>  [449,] 33.333333 #>  [450,] 50.000000 #>  [451,] 33.333333 #>  [452,] 33.333333 #>  [453,]  8.333333 #>  [454,] 33.333333 #>  [455,] 41.666667 #>  [456,] 50.000000 #>  [457,] 41.666667 #>  [458,] 25.000000 #>  [459,] 41.666667 #>  [460,] 41.666667 #>  [461,] 41.666667 #>  [462,] 58.333333 #>  [463,] 50.000000 #>  [464,] 33.333333 #>  [465,] 58.333333 #>  [466,] 16.666667 #>  [467,] 41.666667 #>  [468,] 66.666667 #>  [469,] 33.333333 #>  [470,] 66.666667 #>  [471,] 33.333333 #>  [472,] 33.333333 #>  [473,] 50.000000 #>  [474,] 41.666667 #>  [475,] 66.666667 #>  [476,] 25.000000 #>  [477,] 25.000000 #>  [478,] 33.333333 #>  [479,] 33.333333 #>  [480,] 41.666667 #>  [481,]  8.333333 #>  [482,]  8.333333 #>  [483,] 16.666667 #>  [484,] 41.666667 #>  [485,] 66.666667 #>  [486,]  8.333333 #>  [487,] 25.000000 #>  [488,] 33.333333 #>  [489,] 33.333333 #>  [490,] 33.333333 #>  [491,] 16.666667 #>  [492,] 50.000000 #>  [493,] 66.666667 #>  [494,] 25.000000 #>  [495,] 41.666667 #>  [496,] 41.666667 #>  [497,] 50.000000 #>  [498,] 50.000000 #>  [499,] 25.000000 #>  [500,] 33.333333 #>  [501,] 58.333333 #>  [502,] 50.000000 #>  [503,] 25.000000 #>  [504,] 25.000000 #>  [505,] 25.000000 #>  [506,] 16.666667 #>  [507,] 75.000000 #>  [508,] 41.666667 #>  [509,] 33.333333 #>  [510,] 66.666667 #>  [511,] 33.333333 #>  [512,] 58.333333 #>  [513,] 58.333333 #>  [514,] 66.666667 #>  [515,] 50.000000 #>  [516,] 50.000000 #>  [517,] 16.666667 #>  [518,] 58.333333 #>  [519,] 33.333333 #>  [520,] 25.000000 #>  [521,] 41.666667 #>  [522,] 41.666667 #>  [523,] 66.666667 #>  [524,] 50.000000 #>  [525,] 50.000000 #>  [526,] 33.333333 #>  [527,] 50.000000 #>  [528,] 16.666667 #>  [529,] 66.666667 #>  [530,] 66.666667 #>  [531,] 50.000000 #>  [532,] 33.333333 #>  [533,] 33.333333 #>  [534,] 66.666667 #>  [535,] 41.666667 #>  [536,] 33.333333 #>  [537,] 58.333333 #>  [538,] 66.666667 #>  [539,] 50.000000 #>  [540,] 33.333333 #>  [541,] 25.000000 #>  [542,] 41.666667 #>  [543,] 50.000000 #>  [544,] 66.666667 #>  [545,] 41.666667 #>  [546,]  8.333333 #>  [547,] 50.000000 #>  [548,] 41.666667 #>  [549,] 33.333333 #>  [550,] 50.000000 #>  [551,] 50.000000 #>  [552,] 50.000000 #>  [553,] 33.333333 #>  [554,] 41.666667 #>  [555,] 50.000000 #>  [556,] 50.000000 #>  [557,] 25.000000 #>  [558,]  8.333333 #>  [559,] 50.000000 #>  [560,] 50.000000 #>  [561,] 41.666667 #>  [562,] 41.666667 #>  [563,] 66.666667 #>  [564,] 50.000000 #>  [565,] 25.000000 #>  [566,] 75.000000 #>  [567,] 58.333333 #>  [568,] 41.666667 #>  [569,] 33.333333 #>  [570,] 50.000000 #>  [571,] 50.000000 #>  [572,] 16.666667 #>  [573,] 41.666667 #>  [574,] 33.333333 #>  [575,] 66.666667 #>  [576,] 41.666667 #>  [577,] 58.333333 #>  [578,] 41.666667 #>  [579,] 25.000000 #>  [580,] 50.000000 #>  [581,]  8.333333 #>  [582,] 58.333333 #>  [583,] 50.000000 #>  [584,]  8.333333 #>  [585,] 16.666667 #>  [586,] 41.666667 #>  [587,] 50.000000 #>  [588,] 41.666667 #>  [589,] 41.666667 #>  [590,] 25.000000 #>  [591,] 58.333333 #>  [592,] 33.333333 #>  [593,] 50.000000 #>  [594,] 41.666667 #>  [595,] 66.666667 #>  [596,] 41.666667 #>  [597,] 16.666667 #>  [598,] 33.333333 #>  [599,] 50.000000 #>  [600,] 25.000000 #>  [601,] 33.333333 #>  [602,] 50.000000 #>  [603,] 33.333333 #>  [604,] 25.000000 #>  [605,] 75.000000 #>  [606,] 41.666667 #>  [607,] 25.000000 #>  [608,] 50.000000 #>  [609,] 33.333333 #>  [610,] 50.000000 #>  [611,] 50.000000 #>  [612,] 50.000000 #>  [613,] 16.666667 #>  [614,] 25.000000 #>  [615,] 25.000000 #>  [616,] 33.333333 #>  [617,] 41.666667 #>  [618,] 33.333333 #>  [619,] 41.666667 #>  [620,] 58.333333 #>  [621,] 16.666667 #>  [622,] 33.333333 #>  [623,] 16.666667 #>  [624,] 33.333333 #>  [625,] 58.333333 #>  [626,] 25.000000 #>  [627,] 50.000000 #>  [628,] 50.000000 #>  [629,] 33.333333 #>  [630,] 41.666667 #>  [631,] 41.666667 #>  [632,] 66.666667 #>  [633,] 58.333333 #>  [634,] 50.000000 #>  [635,] 41.666667 #>  [636,] 41.666667 #>  [637,] 25.000000 #>  [638,] 41.666667 #>  [639,] 25.000000 #>  [640,] 66.666667 #>  [641,] 41.666667 #>  [642,] 58.333333 #>  [643,] 16.666667 #>  [644,] 50.000000 #>  [645,] 41.666667 #>  [646,] 58.333333 #>  [647,] 25.000000 #>  [648,] 66.666667 #>  [649,] 50.000000 #>  [650,] 75.000000 #>  [651,] 16.666667 #>  [652,] 50.000000 #>  [653,] 50.000000 #>  [654,] 33.333333 #>  [655,] 50.000000 #>  [656,] 41.666667 #>  [657,] 33.333333 #>  [658,] 50.000000 #>  [659,] 25.000000 #>  [660,] 50.000000 #>  [661,] 41.666667 #>  [662,] 58.333333 #>  [663,] 16.666667 #>  [664,] 58.333333 #>  [665,] 50.000000 #>  [666,] 66.666667 #>  [667,] 50.000000 #>  [668,] 50.000000 #>  [669,] 41.666667 #>  [670,] 33.333333 #>  [671,] 58.333333 #>  [672,] 41.666667 #>  [673,] 50.000000 #>  [674,] 66.666667 #>  [675,] 41.666667 #>  [676,] 16.666667 #>  [677,] 58.333333 #>  [678,] 33.333333 #>  [679,] 50.000000 #>  [680,] 75.000000 #>  [681,] 33.333333 #>  [682,] 58.333333 #>  [683,] 25.000000 #>  [684,] 58.333333 #>  [685,] 33.333333 #>  [686,] 25.000000 #>  [687,] 50.000000 #>  [688,] 25.000000 #>  [689,]  8.333333 #>  [690,] 33.333333 #>  [691,] 41.666667 #>  [692,]  8.333333 #>  [693,] 25.000000 #>  [694,] 50.000000 #>  [695,] 41.666667 #>  [696,] 16.666667 #>  [697,]  8.333333 #>  [698,] 41.666667 #>  [699,] 50.000000 #>  [700,] 66.666667 #>  [701,] 16.666667 #>  [702,] 33.333333 #>  [703,] 50.000000 #>  [704,] 41.666667 #>  [705,] 41.666667 #>  [706,] 50.000000 #>  [707,] 33.333333 #>  [708,] 41.666667 #>  [709,] 33.333333 #>  [710,] 33.333333 #>  [711,] 16.666667 #>  [712,] 58.333333 #>  [713,] 41.666667 #>  [714,] 33.333333 #>  [715,] 50.000000 #>  [716,] 25.000000 #>  [717,] 66.666667 #>  [718,] 33.333333 #>  [719,] 33.333333 #>  [720,] 50.000000 #>  [721,] 58.333333 #>  [722,] 41.666667 #>  [723,] 33.333333 #>  [724,] 41.666667 #>  [725,] 41.666667 #>  [726,] 16.666667 #>  [727,] 25.000000 #>  [728,] 41.666667 #>  [729,] 33.333333 #>  [730,] 33.333333 #>  [731,] 33.333333 #>  [732,] 25.000000 #>  [733,] 33.333333 #>  [734,] 16.666667 #>  [735,] 50.000000 #>  [736,] 50.000000 #>  [737,] 41.666667 #>  [738,] 50.000000 #>  [739,] 41.666667 #>  [740,]  8.333333 #>  [741,] 33.333333 #>  [742,] 25.000000 #>  [743,] 33.333333 #>  [744,] 75.000000 #>  [745,] 41.666667 #>  [746,] 41.666667 #>  [747,] 33.333333 #>  [748,] 41.666667 #>  [749,] 33.333333 #>  [750,] 25.000000 #>  [751,] 41.666667 #>  [752,] 33.333333 #>  [753,] 66.666667 #>  [754,] 33.333333 #>  [755,] 58.333333 #>  [756,] 25.000000 #>  [757,] 41.666667 #>  [758,] 41.666667 #>  [759,] 33.333333 #>  [760,] 16.666667 #>  [761,] 33.333333 #>  [762,] 58.333333 #>  [763,] 50.000000 #>  [764,] 50.000000 #>  [765,] 58.333333 #>  [766,] 50.000000 #>  [767,]  8.333333 #>  [768,] 25.000000 #>  [769,] 41.666667 #>  [770,] 16.666667 #>  [771,] 50.000000 #>  [772,] 50.000000 #>  [773,] 33.333333 #>  [774,] 16.666667 #>  [775,] 25.000000 #>  [776,] 33.333333 #>  [777,] 58.333333 #>  [778,] 41.666667 #>  [779,] 50.000000 #>  [780,] 41.666667 #>  [781,] 33.333333 #>  [782,] 58.333333 #>  [783,] 33.333333 #>  [784,] 25.000000 #>  [785,] 50.000000 #>  [786,] 58.333333 #>  [787,] 41.666667 #>  [788,] 50.000000 #>  [789,] 25.000000 #>  [790,] 50.000000 #>  [791,] 41.666667 #>  [792,] 66.666667 #>  [793,] 41.666667 #>  [794,] 41.666667 #>  [795,] 50.000000 #>  [796,] 41.666667 #>  [797,] 25.000000 #>  [798,] 41.666667 #>  [799,] 25.000000 #>  [800,] 33.333333 #>  [801,] 33.333333 #>  [802,] 25.000000 #>  [803,] 75.000000 #>  [804,] 41.666667 #>  [805,] 41.666667 #>  [806,] 25.000000 #>  [807,] 41.666667 #>  [808,] 25.000000 #>  [809,] 33.333333 #>  [810,] 16.666667 #>  [811,] 25.000000 #>  [812,] 50.000000 #>  [813,] 33.333333 #>  [814,] 16.666667 #>  [815,] 25.000000 #>  [816,] 25.000000 #>  [817,] 33.333333 #>  [818,] 33.333333 #>  [819,] 50.000000 #>  [820,] 41.666667 #>  [821,] 50.000000 #>  [822,] 33.333333 #>  [823,] 50.000000 #>  [824,] 66.666667 #>  [825,] 50.000000 #>  [826,] 41.666667 #>  [827,] 66.666667 #>  [828,] 33.333333 #>  [829,] 33.333333 #>  [830,] 33.333333 #>  [831,] 50.000000 #>  [832,] 33.333333 #>  [833,] 33.333333 #>  [834,] 58.333333 #>  [835,] 33.333333 #>  [836,] 50.000000 #>  [837,] 58.333333 #>  [838,] 66.666667 #>  [839,] 41.666667 #>  [840,] 50.000000 #>  [841,] 16.666667 #>  [842,] 50.000000 #>  [843,] 58.333333 #>  [844,] 25.000000 #>  [845,] 58.333333 #>  [846,] 33.333333 #>  [847,] 50.000000 #>  [848,] 33.333333 #>  [849,] 33.333333 #>  [850,] 50.000000 #>  [851,] 33.333333 #>  [852,] 41.666667 #>  [853,] 50.000000 #>  [854,] 58.333333 #>  [855,] 41.666667 #>  [856,] 33.333333 #>  [857,] 16.666667 #>  [858,] 33.333333 #>  [859,] 33.333333 #>  [860,] 16.666667 #>  [861,] 58.333333 #>  [862,] 41.666667 #>  [863,] 66.666667 #>  [864,] 50.000000 #>  [865,] 50.000000 #>  [866,] 33.333333 #>  [867,] 50.000000 #>  [868,] 50.000000 #>  [869,] 66.666667 #>  [870,] 41.666667 #>  [871,] 41.666667 #>  [872,] 41.666667 #>  [873,] 25.000000 #>  [874,] 33.333333 #>  [875,]  8.333333 #>  [876,] 33.333333 #>  [877,] 41.666667 #>  [878,] 33.333333 #>  [879,] 25.000000 #>  [880,] 33.333333 #>  [881,] 33.333333 #>  [882,] 50.000000 #>  [883,] 41.666667 #>  [884,] 50.000000 #>  [885,] 25.000000 #>  [886,] 41.666667 #>  [887,] 16.666667 #>  [888,] 66.666667 #>  [889,] 41.666667 #>  [890,] 58.333333 #>  [891,] 33.333333 #>  [892,] 50.000000 #>  [893,] 33.333333 #>  [894,] 33.333333 #>  [895,] 25.000000 #>  [896,] 41.666667 #>  [897,] 33.333333 #>  [898,] 50.000000 #>  [899,] 25.000000 #>  [900,] 75.000000 #>  [901,] 16.666667 #>  [902,] 58.333333 #>  [903,] 33.333333 #>  [904,] 41.666667 #>  [905,] 33.333333 #>  [906,] 33.333333 #>  [907,] 50.000000 #>  [908,]  8.333333 #>  [909,] 25.000000 #>  [910,] 25.000000 #>  [911,] 25.000000 #>  [912,] 41.666667 #>  [913,] 25.000000 #>  [914,] 66.666667 #>  [915,] 33.333333 #>  [916,] 33.333333 #>  [917,] 25.000000 #>  [918,] 41.666667 #>  [919,] 25.000000 #>  [920,] 41.666667 #>  [921,] 75.000000 #>  [922,] 50.000000 #>  [923,] 66.666667 #>  [924,] 58.333333 #>  [925,] 33.333333 #>  [926,] 25.000000 #>  [927,] 41.666667 #>  [928,] 50.000000 #>  [929,] 33.333333 #>  [930,] 66.666667 #>  [931,] 25.000000 #>  [932,] 25.000000 #>  [933,] 50.000000 #>  [934,] 58.333333 #>  [935,] 41.666667 #>  [936,] 33.333333 #>  [937,] 41.666667 #>  [938,] 41.666667 #>  [939,] 50.000000 #>  [940,] 33.333333 #>  [941,] 25.000000 #>  [942,] 33.333333 #>  [943,] 66.666667 #>  [944,] 58.333333 #>  [945,] 41.666667 #>  [946,] 33.333333 #>  [947,] 58.333333 #>  [948,] 41.666667 #>  [949,] 50.000000 #>  [950,] 41.666667 #>  [951,] 58.333333 #>  [952,] 33.333333 #>  [953,] 41.666667 #>  [954,] 33.333333 #>  [955,] 58.333333 #>  [956,] 50.000000 #>  [957,] 50.000000 #>  [958,] 33.333333 #>  [959,] 16.666667 #>  [960,] 41.666667 #>  [961,] 41.666667 #>  [962,] 33.333333 #>  [963,] 41.666667 #>  [964,] 50.000000 #>  [965,] 41.666667 #>  [966,] 16.666667 #>  [967,] 58.333333 #>  [968,] 66.666667 #>  [969,] 33.333333 #>  [970,] 41.666667 #>  [971,] 33.333333 #>  [972,] 58.333333 #>  [973,] 58.333333 #>  [974,] 50.000000 #>  [975,] 41.666667 #>  [976,] 33.333333 #>  [977,] 33.333333 #>  [978,] 33.333333 #>  [979,] 33.333333 #>  [980,] 41.666667 #>  [981,] 33.333333 #>  [982,] 50.000000 #>  [983,] 16.666667 #>  [984,] 33.333333 #>  [985,] 58.333333 #>  [986,] 50.000000 #>  [987,] 41.666667 #>  [988,] 66.666667 #>  [989,] 41.666667 #>  [990,] 25.000000 #>  [991,] 33.333333 #>  [992,] 25.000000 #>  [993,] 33.333333 #>  [994,] 25.000000 #>  [995,] 25.000000 #>  [996,] 33.333333 #>  [997,] 16.666667 #>  [998,] 33.333333 #>  [999,] 33.333333 #> [1000,] 41.666667"},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"Prints summary results hypothesis comparison.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"","code":"# S3 method for opaGroupComparison summary(object, ...)"},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"object object class \"opaHypothesisComparison\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"","code":"dat <- data.frame(group = c(\"a\", \"b\", \"a\", \"b\"),                   t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) dat$group <- factor(dat$group, levels = c(\"a\", \"b\")) opamod <- opa(dat[,2:4], 1:3, group = dat$group) z <- compare_groups(opamod, \"a\", \"b\") summary(z) #> ********* Group Comparison ********** #> Group 1: a  #> Group 2: b  #> Group 1 PCC: 33.33333  #> Group 2 PCC: 66.66667  #> PCC difference: 33.33333  #> cval: 0.378"},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"Prints summary results hypothesis comparison.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"","code":"# S3 method for opaHypothesisComparison summary(object, ...)"},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"object object class \"opaHypothesisComparison\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11),                   t4 = c(10, 5, 11, 12)) opamod1 <- opa(dat, c(1, 2, 3, 4)) opamod2 <- opa(dat, c(1, 4, 2, 3)) z <- compare_hypotheses(opamod1, opamod2) summary(z) #> ********* Hypothesis Comparison ********** #> H1: 1 2 3 4  #> H2: 1 4 2 3  #> H1 PCC: 62.5  #> H2 PCC: 66.66667  #> PCC difference: 4.166667  #> cval: 0.916"},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"Prints summary results fitted ordinal pattern analysis model.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"","code":"# S3 method for opafit summary(object, ..., digits = 2L)"},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"object object class \"opafit\". ... ignored digits integer used rounding values output.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) summary(opamod) #> Ordinal Pattern Analysis of 3 observations for 4 individuals in 1 group  #>  #> Between subjects results: #>        PCC  cval #> pooled  50 0.235 #>  #> Within subjects results: #>     PCC cval #> 1  0.00 1.00 #> 2 66.67 0.45 #> 3 66.67 0.50 #> 4 66.67 0.34 #>  #> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0. #> Chance-values were calculated from 1000 random orderings. summary(opamod, digits = 3) #> Ordinal Pattern Analysis of 3 observations for 4 individuals in 1 group  #>  #> Between subjects results: #>        PCC  cval #> pooled  50 0.235 #>  #> Within subjects results: #>      PCC  cval #> 1  0.000 1.000 #> 2 66.667 0.449 #> 3 66.667 0.495 #> 4 66.667 0.337 #>  #> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0. #> Chance-values were calculated from 1000 random orderings."}]
+[{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"GNU General Public License","title":"GNU General Public License","text":"Version 3, 29 June 2007Copyright © 2007 Free Software Foundation, Inc. <http://fsf.org/> Everyone permitted copy distribute verbatim copies license document, changing allowed.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"preamble","dir":"","previous_headings":"","what":"Preamble","title":"GNU General Public License","text":"GNU General Public License free, copyleft license software kinds works. licenses software practical works designed take away freedom share change works. contrast, GNU General Public License intended guarantee freedom share change versions program–make sure remains free software users. , Free Software Foundation, use GNU General Public License software; applies also work released way authors. can apply programs, . speak free software, referring freedom, price. General Public Licenses designed make sure freedom distribute copies free software (charge wish), receive source code can get want , can change software use pieces new free programs, know can things. protect rights, need prevent others denying rights asking surrender rights. Therefore, certain responsibilities distribute copies software, modify : responsibilities respect freedom others. example, distribute copies program, whether gratis fee, must pass recipients freedoms received. must make sure , , receive can get source code. must show terms know rights. Developers use GNU GPL protect rights two steps: (1) assert copyright software, (2) offer License giving legal permission copy, distribute /modify . developers’ authors’ protection, GPL clearly explains warranty free software. users’ authors’ sake, GPL requires modified versions marked changed, problems attributed erroneously authors previous versions. devices designed deny users access install run modified versions software inside , although manufacturer can . fundamentally incompatible aim protecting users’ freedom change software. systematic pattern abuse occurs area products individuals use, precisely unacceptable. Therefore, designed version GPL prohibit practice products. problems arise substantially domains, stand ready extend provision domains future versions GPL, needed protect freedom users. Finally, every program threatened constantly software patents. States allow patents restrict development use software general-purpose computers, , wish avoid special danger patents applied free program make effectively proprietary. prevent , GPL assures patents used render program non-free. precise terms conditions copying, distribution modification follow.","code":""},{"path":[]},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_0-definitions","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"0. Definitions","title":"GNU General Public License","text":"“License” refers version 3 GNU General Public License. “Copyright” also means copyright-like laws apply kinds works, semiconductor masks. “Program” refers copyrightable work licensed License. licensee addressed “”. “Licensees” “recipients” may individuals organizations. “modify” work means copy adapt part work fashion requiring copyright permission, making exact copy. resulting work called “modified version” earlier work work “based ” earlier work. “covered work” means either unmodified Program work based Program. “propagate” work means anything , without permission, make directly secondarily liable infringement applicable copyright law, except executing computer modifying private copy. Propagation includes copying, distribution (without modification), making available public, countries activities well. “convey” work means kind propagation enables parties make receive copies. Mere interaction user computer network, transfer copy, conveying. interactive user interface displays “Appropriate Legal Notices” extent includes convenient prominently visible feature (1) displays appropriate copyright notice, (2) tells user warranty work (except extent warranties provided), licensees may convey work License, view copy License. interface presents list user commands options, menu, prominent item list meets criterion.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_1-source-code","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"1. Source Code","title":"GNU General Public License","text":"“source code” work means preferred form work making modifications . “Object code” means non-source form work. “Standard Interface” means interface either official standard defined recognized standards body, , case interfaces specified particular programming language, one widely used among developers working language. “System Libraries” executable work include anything, work whole, () included normal form packaging Major Component, part Major Component, (b) serves enable use work Major Component, implement Standard Interface implementation available public source code form. “Major Component”, context, means major essential component (kernel, window system, ) specific operating system () executable work runs, compiler used produce work, object code interpreter used run . “Corresponding Source” work object code form means source code needed generate, install, (executable work) run object code modify work, including scripts control activities. However, include work’s System Libraries, general-purpose tools generally available free programs used unmodified performing activities part work. example, Corresponding Source includes interface definition files associated source files work, source code shared libraries dynamically linked subprograms work specifically designed require, intimate data communication control flow subprograms parts work. Corresponding Source need include anything users can regenerate automatically parts Corresponding Source. Corresponding Source work source code form work.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_2-basic-permissions","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"2. Basic Permissions","title":"GNU General Public License","text":"rights granted License granted term copyright Program, irrevocable provided stated conditions met. License explicitly affirms unlimited permission run unmodified Program. output running covered work covered License output, given content, constitutes covered work. License acknowledges rights fair use equivalent, provided copyright law. may make, run propagate covered works convey, without conditions long license otherwise remains force. may convey covered works others sole purpose make modifications exclusively , provide facilities running works, provided comply terms License conveying material control copyright. thus making running covered works must exclusively behalf, direction control, terms prohibit making copies copyrighted material outside relationship . Conveying circumstances permitted solely conditions stated . Sublicensing allowed; section 10 makes unnecessary.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_3-protecting-users-legal-rights-from-anti-circumvention-law","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"3. Protecting Users’ Legal Rights From Anti-Circumvention Law","title":"GNU General Public License","text":"covered work shall deemed part effective technological measure applicable law fulfilling obligations article 11 WIPO copyright treaty adopted 20 December 1996, similar laws prohibiting restricting circumvention measures. convey covered work, waive legal power forbid circumvention technological measures extent circumvention effected exercising rights License respect covered work, disclaim intention limit operation modification work means enforcing, work’s users, third parties’ legal rights forbid circumvention technological measures.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_4-conveying-verbatim-copies","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"4. Conveying Verbatim Copies","title":"GNU General Public License","text":"may convey verbatim copies Program’s source code receive , medium, provided conspicuously appropriately publish copy appropriate copyright notice; keep intact notices stating License non-permissive terms added accord section 7 apply code; keep intact notices absence warranty; give recipients copy License along Program. may charge price price copy convey, may offer support warranty protection fee.","code":""},{"path":"https://timbeechey.github.io/opa/LICENSE.html","id":"id_5-conveying-modified-source-versions","dir":"","previous_headings":"TERMS AND CONDITIONS","what":"5. 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If not, see <http://www.gnu.org/licenses/>. <program>  Copyright (C) <year>  <name of author> This program comes with ABSOLUTELY NO WARRANTY; for details type 'show w'. This is free software, and you are welcome to redistribute it under certain conditions; type 'show c' for details."},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"background","dir":"Articles","previous_headings":"","what":"Background","title":"opa","text":"opa implementation methods described publications including Thorngate (1987) Grice et al. (2015). Thorngate (1987) attributes original idea : Parsons, D. (1975). directory tunes musical themes. S. Brown.","code":""},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"how-ordinal-pattern-analysis-works","dir":"Articles","previous_headings":"","what":"How ordinal pattern analysis works","title":"opa","text":"Ordinal pattern analysis simple non-parametric method, similar Kendall’s Tau. Whereas Kendall’s tau measure similarity two data sets terms rank ordering, ordinal pattern analysis intended quantify match hypothesis patterns individual-level data across conditions measurement instances. Ordinal pattern analysis works comparing relative ordering pairs observations computing whether pairwise relations matched hypothesis. pairwise ordered relation classified increase, decrease, change. classifications encoded 1, -1 0, respectively. example, hypothesis monotonic increase response variable across four experimental conditions can specified : Note absolute values important, relative ordering. hypothesis h encodes six pairwise relations, increases: 1 1 1 1 1 1. row individual data representing measurements across four conditions, : encodes six ordered pairwise relations 1 1 1 -1 1 1. percentage orderings correctly classified hypothesis (PCC) main quantity interest ordinal pattern analysis. Comparing h dat, PCC 5/6 = 0.833 83.3%. hypothesis generates greater PCC preferred hypothesis generates lower PCC given data. also possible calculate chance-value PCC equal chance PCC least great PCC observed data occur result random re-ordering data. Chance values can computed using randomization test.","code":"(h <- c(1, 2, 3, 4)) #> [1] 1 2 3 4 dat <- c(65.3, 68.8, 67.0, 73.1)"},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"modeling-repeated-measures-data","dir":"Articles","previous_headings":"","what":"Modeling repeated measures data","title":"opa","text":"installed, can load opa ","code":"library(opa)"},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"data","dir":"Articles","previous_headings":"Modeling repeated measures data","what":"Data","title":"opa","text":"example use sleepstudy data lme4 package.","code":""},{"path":[]},{"path":[]},{"path":[]},{"path":"https://timbeechey.github.io/opa/articles/opa.html","id":"references","dir":"Articles","previous_headings":"","what":"References","title":"opa","text":"Grice, J. W., Craig, D. P. ., & Abramson, C. . (2015). Simple Transparent Alternative Repeated Measures ANOVA. SAGE Open, 5(3), 215824401560419. https://doi.org/10.1177/2158244015604192 Parsons, D. (1975). directory tunes musical themes. S. Brown. Thorngate, W. (1987). Ordinal Pattern Analysis: Method Assessing Theory-Data Fit. Advances Psychology, 40, 345–364. https://doi.org/10.1016/S0166-4115(08)60083-7","code":""},{"path":"https://timbeechey.github.io/opa/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Timothy Beechey. Author, maintainer.","code":""},{"path":"https://timbeechey.github.io/opa/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Beechey T (2024). opa: Implementation Ordinal Pattern Analysis. R package version 0.8.1.026, https://timbeechey.github.io/opa/.","code":"@Manual{,   title = {opa: An Implementation of Ordinal Pattern Analysis},   author = {Timothy Beechey},   year = {2024},   note = {R package version 0.8.1.026},   url = {https://timbeechey.github.io/opa/}, }"},{"path":"https://timbeechey.github.io/opa/index.html","id":"opa-","dir":"","previous_headings":"","what":"An Implementation of Ordinal Pattern Analysis","title":"An Implementation of Ordinal Pattern Analysis","text":"R package ordinal pattern analysis.","code":""},{"path":"https://timbeechey.github.io/opa/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"An Implementation of Ordinal Pattern Analysis","text":"opa can installed CRAN : can install development version opa GitHub :","code":"install.packages(\"opa\") # install.packages(\"remotes\") remotes::install_github(\"timbeechey/opa\")"},{"path":"https://timbeechey.github.io/opa/index.html","id":"using-opa","dir":"","previous_headings":"","what":"Using opa","title":"An Implementation of Ordinal Pattern Analysis","text":"hypothesized relative ordering response variable across conditions specified numeric vector: hypothesis can visualised plot() function:  Data wide format one column per measurement condition one row per individual: ordinal pattern analysis model hypothesis h matches individual pattern results dat can fitted using: summary model output can viewed using: Individual-level model output can plotted using:  aid interpretation, individual PCCs c-values can also plotted relative user-specified thresholds:","code":"library(opa) (h <- hypothesis(c(1, 2, 4, 3), type = \"pairwise\")) #> ********** Ordinal Hypothesis ********** #> Hypothesis type: pairwise  #> Raw hypothesis: #>  1 2 4 3  #> Ordinal relations: #>  1 1 1 1 1 -1  #> N conditions: 4  #> N hypothesised ordinal relations: 6  #> N hypothesised increases: 5  #> N hypothesised decreases: 1  #> N hypothesised equalities: 0 plot(h) set.seed(123)  dat <- data.frame(t1 = rnorm(20, mean = 12, sd = 2),                   t2 = rnorm(20, mean = 15, sd = 2),                   t3 = rnorm(20, mean = 20, sd = 2),                   t4 = rnorm(20, mean = 17, sd = 2))                    round(dat, 2) #>       t1    t2    t3    t4 #> 1  10.88 12.86 18.61 17.76 #> 2  11.54 14.56 19.58 16.00 #> 3  15.12 12.95 17.47 16.33 #> 4  12.14 13.54 24.34 14.96 #> 5  12.26 13.75 22.42 14.86 #> 6  15.43 11.63 17.75 17.61 #> 7  12.92 16.68 19.19 17.90 #> 8   9.47 15.31 19.07 17.11 #> 9  10.63 12.72 21.56 18.84 #> 10 11.11 17.51 19.83 21.10 #> 11 14.45 15.85 20.51 16.02 #> 12 12.72 14.41 19.94 12.38 #> 13 12.80 16.79 19.91 19.01 #> 14 12.22 16.76 22.74 15.58 #> 15 10.89 16.64 19.55 15.62 #> 16 15.57 16.38 23.03 19.05 #> 17 13.00 16.11 16.90 16.43 #> 18  8.07 14.88 21.17 14.56 #> 19 13.40 14.39 20.25 17.36 #> 20 11.05 14.24 20.43 16.72 opamod <- opa(dat, h) summary(opamod) #> Ordinal Pattern Analysis of 4 observations for 20 individuals in 1 group  #>  #> Between subjects results: #>          PCC cval #> pooled 93.33    0 #>  #> Within subjects results: #>       PCC cval #> 1  100.00 0.04 #> 2  100.00 0.04 #> 3   83.33 0.17 #> 4  100.00 0.05 #> 5  100.00 0.04 #> 6   83.33 0.18 #> 7  100.00 0.04 #> 8  100.00 0.04 #> 9  100.00 0.04 #> 10  83.33 0.15 #> 11 100.00 0.04 #> 12  66.67 0.38 #> 13 100.00 0.04 #> 14  83.33 0.16 #> 15  83.33 0.18 #> 16 100.00 0.04 #> 17 100.00 0.05 #> 18  83.33 0.17 #> 19 100.00 0.04 #> 20 100.00 0.04 #>  #> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0. #> Chance-values were calculated from 1000 random orderings. plot(opamod) plot(opamod, pcc_threshold = 90, cval_threshold = 0.1)"},{"path":"https://timbeechey.github.io/opa/index.html","id":"pairwise-comparison-of-measurement-conditions","dir":"","previous_headings":"Using opa","what":"Pairwise comparison of measurement conditions","title":"An Implementation of Ordinal Pattern Analysis","text":"Pairwise comparisons measurement conditions can calculated applying compare_conditions() function opafit object produced call opa():","code":"condition_comparisons <- compare_conditions(opamod)  print(condition_comparisons) #> Pairwise PCCs: #>     1   2  3 4 #> 1   -   -  - - #> 2  90   -  - - #> 3 100 100  - - #> 4  95  80 95 - #>  #> Pairwise chance values: #>        1      2      3 4 #> 1      -      -      - - #> 2 <0.001      -      - - #> 3 <0.001 <0.001      - - #> 4 <0.001  0.002 <0.001 -"},{"path":"https://timbeechey.github.io/opa/index.html","id":"multiple-groups","dir":"","previous_headings":"Using opa","what":"Multiple groups","title":"An Implementation of Ordinal Pattern Analysis","text":"data consist multiple groups categorical grouping variable can passed group keyword produce results group within data, addition individual results. summary output displays results organised group. Similarly, plotting output shows individual PCCs c-values group.","code":"dat$group <- rep(c(\"A\", \"B\", \"C\", \"D\"), 5) dat$group <- factor(dat$group, levels = c(\"A\", \"B\", \"C\", \"D\"))  opamod2 <- opa(dat[, 1:4], h, group = dat$group) summary(opamod2, digits = 3) #> Ordinal Pattern Analysis of 4 observations for 20 individuals in 4 groups  #>  #> Between subjects results: #>       PCC cval #> A 100.000    0 #> B  86.667    0 #> C  93.333    0 #> D  93.333    0 #>  #> Within subjects results: #>   Individual     PCC  cval #> A          1 100.000 0.034 #> A          5 100.000 0.035 #> A          9 100.000 0.045 #> A         13 100.000 0.044 #> A         17 100.000 0.047 #> B          2 100.000 0.053 #> B          6  83.333 0.191 #> B         10  83.333 0.165 #> B         14  83.333 0.166 #> B         18  83.333 0.159 #> C          3  83.333 0.185 #> C          7 100.000 0.044 #> C         11 100.000 0.043 #> C         15  83.333 0.158 #> C         19 100.000 0.050 #> D          4 100.000 0.055 #> D          8 100.000 0.047 #> D         12  66.667 0.379 #> D         16 100.000 0.050 #> D         20 100.000 0.044 #>  #> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0. #> Chance-values were calculated from 1000 random orderings. plot(opamod2)"},{"path":"https://timbeechey.github.io/opa/index.html","id":"comparing-fit-by-group","dir":"","previous_headings":"Using opa","what":"Comparing fit by group","title":"An Implementation of Ordinal Pattern Analysis","text":"chance-value difference group-level PCCs two groups can calculated using compare_groups() function. difference group-level PCCs along c-value difference can checked:","code":"group_comp <- compare_groups(opamod2, \"A\", \"B\") summary(group_comp) #> ********* Group Comparison ********** #> Group 1: A  #> Group 2: B  #> Group 1 PCC: 100  #> Group 2 PCC: 86.66667  #> PCC difference: 13.33333  #> cval: 0.43"},{"path":"https://timbeechey.github.io/opa/index.html","id":"acknowledgements","dir":"","previous_headings":"","what":"Acknowledgements","title":"An Implementation of Ordinal Pattern Analysis","text":"Development opa supported Medical Research Foundation Fellowship (MRF-049-0004-F-BEEC-C0899).","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"Calculates PCCs c-values based pairwise comparison conditions.","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"","code":"compare_conditions(result, nreps = 1000L)"},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"result object class \"opafit\" produced call opa(). nreps integer","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"compare_conditions returns list following elements pcc_mat lower triangle matrix containing PCCs calculated   pairing data columns. cval_mat lower triangle matrix containing c-values calculated   pairing data columns. pccs vector containing PCCs calculated pairing data. cvals vector containing c-values calculated pairing data. nreps number permutations used calculate c-values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_conditions.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculates PCCs and c-values based on pairwise comparison of conditions. — compare_conditions","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11),                   t4 = c(10, 5, 11, 12)) opamod <- opa(dat, 1:4) compare_conditions(opamod) #> Pairwise PCCs: #>     1  2  3 4 #> 1   -  -  - - #> 2  50  -  - - #> 3  75 25  - - #> 4 100 50 75 - #>  #> Pairwise chance values: #>       1     2    3 4 #> 1     -     -    - - #> 2 0.497     -    - - #> 3 0.318 0.898    - - #> 4 0.052 0.696 0.13 -"},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"Calculate c-value difference PCCs produced two groups","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"","code":"compare_groups(m, group1, group2)"},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"m object class \"opafit\" produced call opa(). group1 character string matches group level passed opa(). group2 character string matches group level passed opa().","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"object class \"opaGroupComparison\".","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_groups.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the c-value of the difference in PCCs produced by two groups — compare_groups","text":"","code":"dat <- data.frame(group = c(\"a\", \"b\", \"a\", \"b\"),                   t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) dat$group <- factor(dat$group, levels = c(\"a\", \"b\")) opamod <- opa(dat[,2:4], 1:3, group = dat$group) compare_groups(opamod, \"a\", \"b\") #> ********* Group Comparison ********** #> Group 1: a  #> Group 2: b  #> Group 1 PCC: 33.33333  #> Group 2 PCC: 66.66667  #> PCC difference: 33.33333  #> cval: 0.42"},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"Calculate c-value difference PCCs produced two hypotheses","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"","code":"compare_hypotheses(m1, m2)"},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"m1 object class \"opafit\" produced call opa(). m2 object class \"opafit\" produced call opa().","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"object class \"opaHypothesisComparison\".","code":""},{"path":"https://timbeechey.github.io/opa/reference/compare_hypotheses.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Calculate the c-value of the difference in PCCs produced by two hypotheses — compare_hypotheses","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11),                   t4 = c(10, 5, 11, 12)) opamod1 <- opa(dat, c(1, 2, 3, 4)) opamod2 <- opa(dat, c(1, 4, 2, 3)) compare_hypotheses(opamod1, opamod2) #> ********* Hypothesis Comparison ********** #> H1: 1 2 3 4  #> H2: 1 4 2 3  #> H1 PCC: 62.5  #> H2 PCC: 66.66667  #> PCC difference: 4.166667  #> cval: 0.895"},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"Return number pairs observations matched hypothesis","code":""},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"","code":"correct_pairs(m)"},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"non-negative integer","code":""},{"path":"https://timbeechey.github.io/opa/reference/correct_pairs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the number of pairs of observations matched by the hypothesis — correct_pairs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) correct_pairs(opamod) #> [1] 6"},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot individual chance values — cval_plot","title":"Plot individual chance values — cval_plot","text":"Plot individual chance values","code":""},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot individual chance values — cval_plot","text":"","code":"cval_plot(m, threshold = NULL, title = TRUE, legend = TRUE)"},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot individual chance values — cval_plot","text":"m object class \"opafit\" threshold boolean indicating whether plot threshold abline title boolean indicating whether include plot title legend boolean indicating whether include legend n groups > 1","code":""},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot individual chance values — cval_plot","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/cval_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot individual chance values — cval_plot","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) cval_plot(opamod)  cval_plot(opamod, threshold = 0.1)"},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the group chance values of the specified model — group_cvals","title":"Return the group chance values of the specified model — group_cvals","text":"Return group chance values specified model","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the group chance values of the specified model — group_cvals","text":"","code":"group_cvals(m)"},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the group chance values of the specified model — group_cvals","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the group chance values of the specified model — group_cvals","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_cvals.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the group chance values of the specified model — group_cvals","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) group_cvals(opamod) #> [1] 0.241"},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the group PCCs of the specified model — group_pccs","title":"Return the group PCCs of the specified model — group_pccs","text":"Return group PCCs specified model","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the group PCCs of the specified model — group_pccs","text":"","code":"group_pccs(m)"},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the group PCCs of the specified model — group_pccs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the group PCCs of the specified model — group_pccs","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_pccs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the group PCCs of the specified model — group_pccs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) group_pccs(opamod) #> [1] 50"},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Group-level PCC and chance values. — group_results","title":"Group-level PCC and chance values. — group_results","text":"Group-level PCC chance values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Group-level PCC and chance values. — group_results","text":"","code":"group_results(m, digits)"},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Group-level PCC and chance values. — group_results","text":"m object class \"opafit\" produced opa(). digits positive integer.","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Group-level PCC and chance values. — group_results","text":"matrix 1 row per group.","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Group-level PCC and chance values. — group_results","text":"model fitted grouping variable, single PCC c-value returned. grouping variable specified call opa PCCs c-values returned factor level grouping variable.","code":""},{"path":"https://timbeechey.github.io/opa/reference/group_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Group-level PCC and chance values. — group_results","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) group_results(opamod) #>        PCC  cval #> pooled  50 0.247"},{"path":"https://timbeechey.github.io/opa/reference/hypothesis.html","id":null,"dir":"Reference","previous_headings":"","what":"create a hypothesis object — hypothesis","title":"create a hypothesis object — hypothesis","text":"create hypothesis object","code":""},{"path":"https://timbeechey.github.io/opa/reference/hypothesis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"create a hypothesis object — hypothesis","text":"","code":"hypothesis(xs, type = \"pairwise\")"},{"path":"https://timbeechey.github.io/opa/reference/hypothesis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"create a hypothesis object — hypothesis","text":"xs numeric vector type string","code":""},{"path":"https://timbeechey.github.io/opa/reference/hypothesis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"create a hypothesis object — hypothesis","text":"list containing following elements","code":""},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"Return number pairs observations matched hypothesis","code":""},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"","code":"incorrect_pairs(m)"},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"non-negative integer","code":""},{"path":"https://timbeechey.github.io/opa/reference/incorrect_pairs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the number of pairs of observations not matched by the hypothesis — incorrect_pairs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) incorrect_pairs(opamod) #> [1] 6"},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the individual chance values of the specified model — individual_cvals","title":"Return the individual chance values of the specified model — individual_cvals","text":"Return individual chance values specified model","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the individual chance values of the specified model — individual_cvals","text":"","code":"individual_cvals(m)"},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the individual chance values of the specified model — individual_cvals","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the individual chance values of the specified model — individual_cvals","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_cvals.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the individual chance values of the specified model — individual_cvals","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) individual_cvals(opamod) #> [1] 1.000 0.512 0.480 0.318"},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the individual PCCs of the specified model — individual_pccs","title":"Return the individual PCCs of the specified model — individual_pccs","text":"Return individual PCCs specified model","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the individual PCCs of the specified model — individual_pccs","text":"","code":"individual_pccs(m)"},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the individual PCCs of the specified model — individual_pccs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the individual PCCs of the specified model — individual_pccs","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_pccs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the individual PCCs of the specified model — individual_pccs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) individual_pccs(opamod) #> [1]  0.00000 66.66667 66.66667 66.66667"},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":null,"dir":"Reference","previous_headings":"","what":"Individual-level PCC and chance values. — individual_results","title":"Individual-level PCC and chance values. — individual_results","text":"Individual-level PCC chance values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Individual-level PCC and chance values. — individual_results","text":"","code":"individual_results(m, digits)"},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Individual-level PCC and chance values. — individual_results","text":"m object class \"opafit\" produced opa() digits integer","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Individual-level PCC and chance values. — individual_results","text":"matrix containing column PCC values column c-values 1 row per row data.","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Individual-level PCC and chance values. — individual_results","text":"opa model fitted grouping variable, matrix PCCs c-values returned corresponding order rows data. opa model fitted grouping variable specified, table PCCs c-values returned ordered factor level grouping variable.","code":""},{"path":"https://timbeechey.github.io/opa/reference/individual_results.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Individual-level PCC and chance values. — individual_results","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) individual_results(opamod) #>     PCC cval #> 1  0.00 1.00 #> 2 66.67 0.52 #> 3 66.67 0.55 #> 4 66.67 0.35"},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":null,"dir":"Reference","previous_headings":"","what":"Fit an ordinal pattern analysis model — opa","title":"Fit an ordinal pattern analysis model — opa","text":"opa used fit ordinal pattern analysis models computing percentage pair orderings row data matched corresponding pair orderings hypothesis, addition chance permutation data producing percentage match great.","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fit an ordinal pattern analysis model — opa","text":"","code":"opa(   dat,   hypothesis,   group = NULL,   pairing_type = \"pairwise\",   diff_threshold = 0,   nreps = 1000L )"},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fit an ordinal pattern analysis model — opa","text":"dat data frame hypothesis numeric vector group optional factor vector pairing_type string diff_threshold positive integer floating point number nreps integer, ignored cval_method = \"exact\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fit an ordinal pattern analysis model — opa","text":"opa returns object class \"opafit\". object class \"opafit\" list containing folllowing components: group_pcc percentage pairwise orderings pooled data   rows correctly classified hypothesis. individual_pccs vector containing percentage pairwise   orderings correctly classified hypothesis data   row. correct_pairs integer representing number pairwise   orderings pooled across data rows correctly classified   hypothesis. total_pairs integer, number pair orderings contained   data. group_cval group-level chance value. individual_cvals vector containing chance values data   row rand_pccs vector PCCS calculated random ordering   length equal nreps, list vectors group vector   passed opa(). call matched call hypothesis hypothesis vector passed opa() pairing_type string indicating method pairing passed   opa(). diff_threshold numeric difference threshold used calculate   PCCs. value passed diff_threshold, default   0 used. data data.frame passed opa(). groups vector groups passed opa. group vector   passed opa() default NULL used. nreps integer, number random re-orderings data   used compute chance values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fit an ordinal pattern analysis model — opa","text":"Data expected wide format 1 row per individual 1 column per measurement condition. Data must contain columns consisting numerical values dependent variable. length hypothesis must equal number columns dependent variable data.frame dat. independent variable must passed separately vector group keyword. grouping vector must factor. pairing_type must either \"pairwise\" \"adjacent\". \"pairwise\" option considered relative ordering every pair observations data every pair elements hypothesis. \"adjacent\" option considers ordering adjacent pairs . unspecified, default \"pairwise\". diff_threshold may positive integer double. unspecified default zero threshold used. diff_threshold never applied hypothesis. nreps specifies number random reorderigs use calculation chance-values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Fit an ordinal pattern analysis model — opa","text":"Grice, J. W., Craig, D. P. ., & Abramson, C. . (2015). Simple Transparent Alternative Repeated Measures ANOVA. SAGE Open, 5(3), 215824401560419. <https://doi.org/10.1177/2158244015604192> Thorngate, W. (1987). Ordinal Pattern Analysis: Method Assessing Theory-Data Fit. Advances Psychology, 40, 345–364. <https://doi.org/10.1016/S0166-4115(08)60083-7>","code":""},{"path":"https://timbeechey.github.io/opa/reference/opa.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fit an ordinal pattern analysis model — opa","text":"","code":"dat <- data.frame(group = c(\"a\", \"b\", \"a\", \"b\"),                   t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) dat$group <- factor(dat$group, levels = c(\"a\", \"b\")) opamod <- opa(dat[,2:4], 1:3) opa(dat[,2:4], 1:3) #> opa(dat = dat[, 2:4], hypothesis = 1:3) opa(dat[,2:4], 1:3, nreps = 500) #> opa(dat = dat[, 2:4], hypothesis = 1:3, nreps = 500) opa(dat[,2:4], 1:3, pairing_type = \"adjacent\") #> opa(dat = dat[, 2:4], hypothesis = 1:3, pairing_type = \"adjacent\") opa(dat[,2:4], 1:3, diff_threshold = 1) #> opa(dat = dat[, 2:4], hypothesis = 1:3, diff_threshold = 1) opa(dat[,2:4], 1:3, group = dat$group) #> opa(dat = dat[, 2:4], hypothesis = 1:3, group = dat$group)"},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot individual PCCs. — pcc_plot","title":"Plot individual PCCs. — pcc_plot","text":"Plot individual PCCs.","code":""},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot individual PCCs. — pcc_plot","text":"","code":"pcc_plot(m, threshold = NULL, title = TRUE, legend = TRUE)"},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot individual PCCs. — pcc_plot","text":"m object class \"opafit\" threshold boolean indicating whether plot threshold abline title boolean indicating whether include plot title legend boolean indicating whether include legend","code":""},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot individual PCCs. — pcc_plot","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/pcc_plot.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot individual PCCs. — pcc_plot","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) pcc_plot(opamod)  pcc_plot(opamod, threshold = 85)"},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":null,"dir":"Reference","previous_headings":"","what":"Plots individual-level PCCs and chance-values. — plot.opafit","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"Plots individual-level PCCs chance-values.","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"","code":"# S3 method for opafit plot(x, pcc_threshold = NULL, cval_threshold = NULL, ...)"},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"x object class \"opafit\" produced opa() pcc_threshold number used x-intercept plot PCC threshold abline cval_threshold number used x-intercept plot c-value threshold abline ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opafit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plots individual-level PCCs and chance-values. — plot.opafit","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) plot(opamod)"},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot a hypothesis. — plot.opahypothesis","title":"Plot a hypothesis. — plot.opahypothesis","text":"Plot hypothesis.","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot a hypothesis. — plot.opahypothesis","text":"","code":"# S3 method for opahypothesis plot(x, title = TRUE, ...)"},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot a hypothesis. — plot.opahypothesis","text":"x object class \"opaHypothesis\" title boolean indicating whether include plot title ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot a hypothesis. — plot.opahypothesis","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/plot.opahypothesis.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Plot a hypothesis. — plot.opahypothesis","text":"","code":"h <- hypothesis(c(1,2,3,3,3)) plot(h)"},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"Prints summary results hypothesis comparison.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"","code":"# S3 method for opaGroupComparison print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"x object class \"opaHypothesisComparison\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaGroupComparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from hypothesis comparison. — print.opaGroupComparison","text":"","code":"dat <- data.frame(group = c(\"a\", \"b\", \"a\", \"b\"),                   t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) dat$group <- factor(dat$group, levels = c(\"a\", \"b\")) opamod <- opa(dat[,2:4], 1:3, group = dat$group) z <- compare_groups(opamod, \"a\", \"b\") print(z) #> ********* Group Comparison ********** #> Group 1: a  #> Group 2: b  #> Group 1 PCC: 33.33333  #> Group 2 PCC: 66.66667  #> PCC difference: 33.33333  #> cval: 0.371"},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"Prints summary results hypothesis comparison.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"","code":"# S3 method for opaHypothesisComparison print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"x object class \"opaHypothesisComparison\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opaHypothesisComparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from hypothesis comparison. — print.opaHypothesisComparison","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11),                   t4 = c(10, 5, 11, 12)) opamod1 <- opa(dat, c(1, 2, 3, 4)) opamod2 <- opa(dat, c(1, 4, 2, 3)) z <- compare_hypotheses(opamod1, opamod2) print(z) #> ********* Hypothesis Comparison ********** #> H1: 1 2 3 4  #> H2: 1 4 2 3  #> H1 PCC: 62.5  #> H2 PCC: 66.66667  #> PCC difference: 4.166667  #> cval: 0.886"},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":null,"dir":"Reference","previous_headings":"","what":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"Displays call used fit ordinal pattern analysis model.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"","code":"# S3 method for opafit print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"x object class \"opafit\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opafit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Displays the call used to fit an ordinal pattern analysis model. — print.opafit","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) print(opamod) #> opa(dat = dat, hypothesis = 1:3)"},{"path":"https://timbeechey.github.io/opa/reference/print.opahypothesis.html","id":null,"dir":"Reference","previous_headings":"","what":"Print details of a hypothesis — print.opahypothesis","title":"Print details of a hypothesis — print.opahypothesis","text":"Print details hypothesis","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opahypothesis.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print details of a hypothesis — print.opahypothesis","text":"","code":"# S3 method for opahypothesis print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.opahypothesis.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print details of a hypothesis — print.opahypothesis","text":"x object type \"opaHypothesis\" ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.opahypothesis.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print details of a hypothesis — print.opahypothesis","text":"return value, called side-effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":null,"dir":"Reference","previous_headings":"","what":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"Displays results pairwise ordinal pattern analysis.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"","code":"# S3 method for pairwiseopafit print(x, ...)"},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"x object class \"pairwiseopafit\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/print.pairwiseopafit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Displays the results of a pairwise ordinal pattern analysis. — print.pairwiseopafit","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) pw <- compare_conditions(opamod) print(pw) #> Pairwise PCCs: #>    1  2 3 #> 1  -  - - #> 2 50  - - #> 3 75 25 - #>  #> Pairwise chance values: #>       1     2 3 #> 1     -     - - #> 2 0.516     - - #> 3 0.318 0.878 - print(pw, digits = 2) #> Pairwise PCCs: #>    1  2 3 #> 1  -  - - #> 2 50  - - #> 3 75 25 - #>  #> Pairwise chance values: #>       1     2 3 #> 1     -     - - #> 2 0.516     - - #> 3 0.318 0.878 -"},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":null,"dir":"Reference","previous_headings":"","what":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"Return random order generated PCCs used calculate group chance value","code":""},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"","code":"random_pccs(m)"},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"m object class \"opafit\"","code":""},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"numeric vector","code":""},{"path":"https://timbeechey.github.io/opa/reference/random_pccs.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Return the random order generated PCCs used to calculate the group chance value — random_pccs","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) random_pccs(opamod) #>              [,1] #>    [1,] 50.000000 #>    [2,] 50.000000 #>    [3,] 25.000000 #>    [4,] 25.000000 #>    [5,] 41.666667 #>    [6,] 33.333333 #>    [7,] 41.666667 #>    [8,] 33.333333 #>    [9,] 58.333333 #>   [10,] 41.666667 #>   [11,] 41.666667 #>   [12,]  8.333333 #>   [13,] 58.333333 #>   [14,] 58.333333 #>   [15,] 41.666667 #>   [16,] 33.333333 #>   [17,] 58.333333 #>   [18,]  8.333333 #>   [19,] 25.000000 #>   [20,] 66.666667 #>   [21,] 25.000000 #>   [22,] 50.000000 #>   [23,] 25.000000 #>   [24,] 41.666667 #>   [25,] 25.000000 #>   [26,] 33.333333 #>   [27,] 50.000000 #>   [28,] 41.666667 #>   [29,] 41.666667 #>   [30,] 41.666667 #>   [31,]  8.333333 #>   [32,] 41.666667 #>   [33,] 58.333333 #>   [34,] 50.000000 #>   [35,] 33.333333 #>   [36,] 50.000000 #>   [37,] 33.333333 #>   [38,] 66.666667 #>   [39,] 41.666667 #>   [40,] 41.666667 #>   [41,] 50.000000 #>   [42,] 41.666667 #>   [43,] 50.000000 #>   [44,] 33.333333 #>   [45,] 33.333333 #>   [46,] 16.666667 #>   [47,] 50.000000 #>   [48,] 16.666667 #>   [49,] 25.000000 #>   [50,] 58.333333 #>   [51,] 25.000000 #>   [52,] 33.333333 #>   [53,] 41.666667 #>   [54,] 33.333333 #>   [55,] 66.666667 #>   [56,] 25.000000 #>   [57,] 41.666667 #>   [58,] 41.666667 #>   [59,] 33.333333 #>   [60,] 25.000000 #>   [61,] 33.333333 #>   [62,] 33.333333 #>   [63,] 25.000000 #>   [64,] 41.666667 #>   [65,] 41.666667 #>   [66,]  0.000000 #>   [67,] 25.000000 #>   [68,] 66.666667 #>   [69,] 25.000000 #>   [70,] 41.666667 #>   [71,] 33.333333 #>   [72,] 33.333333 #>   [73,] 25.000000 #>   [74,] 41.666667 #>   [75,] 41.666667 #>   [76,] 50.000000 #>   [77,] 50.000000 #>   [78,] 33.333333 #>   [79,] 33.333333 #>   [80,] 33.333333 #>   [81,] 66.666667 #>   [82,] 50.000000 #>   [83,] 58.333333 #>   [84,] 33.333333 #>   [85,] 50.000000 #>   [86,] 33.333333 #>   [87,] 33.333333 #>   [88,] 41.666667 #>   [89,] 33.333333 #>   [90,] 16.666667 #>   [91,] 25.000000 #>   [92,] 58.333333 #>   [93,] 50.000000 #>   [94,] 25.000000 #>   [95,] 41.666667 #>   [96,] 41.666667 #>   [97,] 16.666667 #>   [98,] 50.000000 #>   [99,] 50.000000 #>  [100,] 33.333333 #>  [101,] 58.333333 #>  [102,] 33.333333 #>  [103,] 33.333333 #>  [104,] 33.333333 #>  [105,] 41.666667 #>  [106,] 50.000000 #>  [107,] 50.000000 #>  [108,] 50.000000 #>  [109,] 33.333333 #>  [110,] 41.666667 #>  [111,]  8.333333 #>  [112,] 66.666667 #>  [113,] 33.333333 #>  [114,] 58.333333 #>  [115,] 75.000000 #>  [116,] 41.666667 #>  [117,] 33.333333 #>  [118,] 66.666667 #>  [119,] 41.666667 #>  [120,] 16.666667 #>  [121,] 50.000000 #>  [122,] 41.666667 #>  [123,] 58.333333 #>  [124,] 50.000000 #>  [125,] 41.666667 #>  [126,] 25.000000 #>  [127,] 50.000000 #>  [128,] 33.333333 #>  [129,] 33.333333 #>  [130,] 41.666667 #>  [131,] 41.666667 #>  [132,] 16.666667 #>  [133,] 66.666667 #>  [134,] 41.666667 #>  [135,] 25.000000 #>  [136,] 41.666667 #>  [137,] 33.333333 #>  [138,] 41.666667 #>  [139,] 33.333333 #>  [140,] 58.333333 #>  [141,] 58.333333 #>  [142,] 33.333333 #>  [143,] 50.000000 #>  [144,] 33.333333 #>  [145,] 33.333333 #>  [146,] 50.000000 #>  [147,] 58.333333 #>  [148,] 50.000000 #>  [149,] 50.000000 #>  [150,] 50.000000 #>  [151,] 25.000000 #>  [152,] 41.666667 #>  [153,] 16.666667 #>  [154,] 16.666667 #>  [155,] 25.000000 #>  [156,] 16.666667 #>  [157,] 16.666667 #>  [158,] 25.000000 #>  [159,] 33.333333 #>  [160,] 33.333333 #>  [161,] 41.666667 #>  [162,] 25.000000 #>  [163,] 33.333333 #>  [164,] 33.333333 #>  [165,]  8.333333 #>  [166,] 41.666667 #>  [167,] 75.000000 #>  [168,] 41.666667 #>  [169,] 50.000000 #>  [170,] 41.666667 #>  [171,] 25.000000 #>  [172,] 50.000000 #>  [173,] 33.333333 #>  [174,] 41.666667 #>  [175,] 25.000000 #>  [176,] 41.666667 #>  [177,] 58.333333 #>  [178,] 25.000000 #>  [179,] 33.333333 #>  [180,] 33.333333 #>  [181,] 58.333333 #>  [182,] 33.333333 #>  [183,] 50.000000 #>  [184,]  8.333333 #>  [185,] 50.000000 #>  [186,] 41.666667 #>  [187,] 33.333333 #>  [188,] 50.000000 #>  [189,] 50.000000 #>  [190,] 66.666667 #>  [191,] 25.000000 #>  [192,] 66.666667 #>  [193,] 25.000000 #>  [194,] 25.000000 #>  [195,] 16.666667 #>  [196,] 83.333333 #>  [197,] 41.666667 #>  [198,] 50.000000 #>  [199,] 50.000000 #>  [200,] 41.666667 #>  [201,]  8.333333 #>  [202,] 33.333333 #>  [203,] 50.000000 #>  [204,] 16.666667 #>  [205,] 25.000000 #>  [206,] 41.666667 #>  [207,] 58.333333 #>  [208,] 41.666667 #>  [209,] 50.000000 #>  [210,] 33.333333 #>  [211,] 33.333333 #>  [212,] 66.666667 #>  [213,] 50.000000 #>  [214,] 58.333333 #>  [215,] 41.666667 #>  [216,] 50.000000 #>  [217,] 33.333333 #>  [218,] 50.000000 #>  [219,] 58.333333 #>  [220,] 25.000000 #>  [221,] 25.000000 #>  [222,] 33.333333 #>  [223,] 41.666667 #>  [224,] 41.666667 #>  [225,] 50.000000 #>  [226,] 33.333333 #>  [227,] 58.333333 #>  [228,] 25.000000 #>  [229,] 41.666667 #>  [230,] 50.000000 #>  [231,] 58.333333 #>  [232,] 16.666667 #>  [233,] 58.333333 #>  [234,] 33.333333 #>  [235,] 33.333333 #>  [236,] 33.333333 #>  [237,] 33.333333 #>  [238,] 66.666667 #>  [239,] 58.333333 #>  [240,] 50.000000 #>  [241,] 25.000000 #>  [242,] 50.000000 #>  [243,] 33.333333 #>  [244,] 41.666667 #>  [245,] 50.000000 #>  [246,] 25.000000 #>  [247,] 58.333333 #>  [248,] 58.333333 #>  [249,] 41.666667 #>  [250,] 50.000000 #>  [251,] 66.666667 #>  [252,] 50.000000 #>  [253,] 41.666667 #>  [254,] 41.666667 #>  [255,]  8.333333 #>  [256,] 25.000000 #>  [257,] 41.666667 #>  [258,] 25.000000 #>  [259,] 33.333333 #>  [260,] 50.000000 #>  [261,] 33.333333 #>  [262,] 50.000000 #>  [263,] 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33.333333 #>  [834,] 58.333333 #>  [835,] 33.333333 #>  [836,] 50.000000 #>  [837,] 58.333333 #>  [838,] 66.666667 #>  [839,] 41.666667 #>  [840,] 50.000000 #>  [841,] 16.666667 #>  [842,] 50.000000 #>  [843,] 58.333333 #>  [844,] 25.000000 #>  [845,] 58.333333 #>  [846,] 33.333333 #>  [847,] 50.000000 #>  [848,] 33.333333 #>  [849,] 33.333333 #>  [850,] 50.000000 #>  [851,] 33.333333 #>  [852,] 41.666667 #>  [853,] 50.000000 #>  [854,] 58.333333 #>  [855,] 41.666667 #>  [856,] 33.333333 #>  [857,] 16.666667 #>  [858,] 33.333333 #>  [859,] 33.333333 #>  [860,] 16.666667 #>  [861,] 58.333333 #>  [862,] 41.666667 #>  [863,] 66.666667 #>  [864,] 50.000000 #>  [865,] 50.000000 #>  [866,] 33.333333 #>  [867,] 50.000000 #>  [868,] 50.000000 #>  [869,] 66.666667 #>  [870,] 41.666667 #>  [871,] 41.666667 #>  [872,] 41.666667 #>  [873,] 25.000000 #>  [874,] 33.333333 #>  [875,]  8.333333 #>  [876,] 33.333333 #>  [877,] 41.666667 #>  [878,] 33.333333 #>  [879,] 25.000000 #>  [880,] 33.333333 #>  [881,] 33.333333 #>  [882,] 50.000000 #>  [883,] 41.666667 #>  [884,] 50.000000 #>  [885,] 25.000000 #>  [886,] 41.666667 #>  [887,] 16.666667 #>  [888,] 66.666667 #>  [889,] 41.666667 #>  [890,] 58.333333 #>  [891,] 33.333333 #>  [892,] 50.000000 #>  [893,] 33.333333 #>  [894,] 33.333333 #>  [895,] 25.000000 #>  [896,] 41.666667 #>  [897,] 33.333333 #>  [898,] 50.000000 #>  [899,] 25.000000 #>  [900,] 75.000000 #>  [901,] 16.666667 #>  [902,] 58.333333 #>  [903,] 33.333333 #>  [904,] 41.666667 #>  [905,] 33.333333 #>  [906,] 33.333333 #>  [907,] 50.000000 #>  [908,]  8.333333 #>  [909,] 25.000000 #>  [910,] 25.000000 #>  [911,] 25.000000 #>  [912,] 41.666667 #>  [913,] 25.000000 #>  [914,] 66.666667 #>  [915,] 33.333333 #>  [916,] 33.333333 #>  [917,] 25.000000 #>  [918,] 41.666667 #>  [919,] 25.000000 #>  [920,] 41.666667 #>  [921,] 75.000000 #>  [922,] 50.000000 #>  [923,] 66.666667 #>  [924,] 58.333333 #>  [925,] 33.333333 #>  [926,] 25.000000 #>  [927,] 41.666667 #>  [928,] 50.000000 #>  [929,] 33.333333 #>  [930,] 66.666667 #>  [931,] 25.000000 #>  [932,] 25.000000 #>  [933,] 50.000000 #>  [934,] 58.333333 #>  [935,] 41.666667 #>  [936,] 33.333333 #>  [937,] 41.666667 #>  [938,] 41.666667 #>  [939,] 50.000000 #>  [940,] 33.333333 #>  [941,] 25.000000 #>  [942,] 33.333333 #>  [943,] 66.666667 #>  [944,] 58.333333 #>  [945,] 41.666667 #>  [946,] 33.333333 #>  [947,] 58.333333 #>  [948,] 41.666667 #>  [949,] 50.000000 #>  [950,] 41.666667 #>  [951,] 58.333333 #>  [952,] 33.333333 #>  [953,] 41.666667 #>  [954,] 33.333333 #>  [955,] 58.333333 #>  [956,] 50.000000 #>  [957,] 50.000000 #>  [958,] 33.333333 #>  [959,] 16.666667 #>  [960,] 41.666667 #>  [961,] 41.666667 #>  [962,] 33.333333 #>  [963,] 41.666667 #>  [964,] 50.000000 #>  [965,] 41.666667 #>  [966,] 16.666667 #>  [967,] 58.333333 #>  [968,] 66.666667 #>  [969,] 33.333333 #>  [970,] 41.666667 #>  [971,] 33.333333 #>  [972,] 58.333333 #>  [973,] 58.333333 #>  [974,] 50.000000 #>  [975,] 41.666667 #>  [976,] 33.333333 #>  [977,] 33.333333 #>  [978,] 33.333333 #>  [979,] 33.333333 #>  [980,] 41.666667 #>  [981,] 33.333333 #>  [982,] 50.000000 #>  [983,] 16.666667 #>  [984,] 33.333333 #>  [985,] 58.333333 #>  [986,] 50.000000 #>  [987,] 41.666667 #>  [988,] 66.666667 #>  [989,] 41.666667 #>  [990,] 25.000000 #>  [991,] 33.333333 #>  [992,] 25.000000 #>  [993,] 33.333333 #>  [994,] 25.000000 #>  [995,] 25.000000 #>  [996,] 33.333333 #>  [997,] 16.666667 #>  [998,] 33.333333 #>  [999,] 33.333333 #> [1000,] 41.666667"},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"Prints summary results hypothesis comparison.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"","code":"# S3 method for opaGroupComparison summary(object, ...)"},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"object object class \"opaHypothesisComparison\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaGroupComparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from hypothesis comparison. — summary.opaGroupComparison","text":"","code":"dat <- data.frame(group = c(\"a\", \"b\", \"a\", \"b\"),                   t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) dat$group <- factor(dat$group, levels = c(\"a\", \"b\")) opamod <- opa(dat[,2:4], 1:3, group = dat$group) z <- compare_groups(opamod, \"a\", \"b\") summary(z) #> ********* Group Comparison ********** #> Group 1: a  #> Group 2: b  #> Group 1 PCC: 33.33333  #> Group 2 PCC: 66.66667  #> PCC difference: 33.33333  #> cval: 0.378"},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"Prints summary results hypothesis comparison.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"","code":"# S3 method for opaHypothesisComparison summary(object, ...)"},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"object object class \"opaHypothesisComparison\". ... ignored","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opaHypothesisComparison.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from hypothesis comparison. — summary.opaHypothesisComparison","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11),                   t4 = c(10, 5, 11, 12)) opamod1 <- opa(dat, c(1, 2, 3, 4)) opamod2 <- opa(dat, c(1, 4, 2, 3)) z <- compare_hypotheses(opamod1, opamod2) summary(z) #> ********* Hypothesis Comparison ********** #> H1: 1 2 3 4  #> H2: 1 4 2 3  #> H1 PCC: 62.5  #> H2 PCC: 66.66667  #> PCC difference: 4.166667  #> cval: 0.916"},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":null,"dir":"Reference","previous_headings":"","what":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"Prints summary results fitted ordinal pattern analysis model.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"","code":"# S3 method for opafit summary(object, ..., digits = 2L)"},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"object object class \"opafit\". ... ignored digits integer used rounding values output.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"return value, called side effects.","code":""},{"path":"https://timbeechey.github.io/opa/reference/summary.opafit.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Prints a summary of results from a fitted ordinal pattern analysis model. — summary.opafit","text":"","code":"dat <- data.frame(t1 = c(9, 4, 8, 10),                   t2 = c(8, 8, 12, 10),                   t3 = c(8, 5, 10, 11)) opamod <- opa(dat, 1:3) summary(opamod) #> Ordinal Pattern Analysis of 3 observations for 4 individuals in 1 group  #>  #> Between subjects results: #>        PCC  cval #> pooled  50 0.235 #>  #> Within subjects results: #>     PCC cval #> 1  0.00 1.00 #> 2 66.67 0.45 #> 3 66.67 0.50 #> 4 66.67 0.34 #>  #> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0. #> Chance-values were calculated from 1000 random orderings. summary(opamod, digits = 3) #> Ordinal Pattern Analysis of 3 observations for 4 individuals in 1 group  #>  #> Between subjects results: #>        PCC  cval #> pooled  50 0.235 #>  #> Within subjects results: #>      PCC  cval #> 1  0.000 1.000 #> 2 66.667 0.449 #> 3 66.667 0.495 #> 4 66.667 0.337 #>  #> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0. #> Chance-values were calculated from 1000 random orderings."}]