diff --git a/DESCRIPTION b/DESCRIPTION
index c335bcd..baebce5 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,7 +1,7 @@
Package: opa
Type: Package
Title: An Implementation of Ordinal Pattern Analysis
-Version: 0.8.2.026
+Version: 0.8.2.027
Authors@R: person("Timothy", "Beechey", email = "tim.beechey@proton.me",
role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8858-946X"))
Description: Quantifies hypothesis to data fit for repeated measures
diff --git a/README.Rmd b/README.Rmd
index bbedf8e..68b5c35 100644
--- a/README.Rmd
+++ b/README.Rmd
@@ -12,7 +12,7 @@ knitr::opts_chunk$set(
)
# set plot colors
-palette(c("#0072B2", "#999999", "#E69F00", "#56B4E9"))
+palette(c("#0073C2FF", "#EFC000FF", "#868686FF", "#CD534CFF"))
```
# opa
@@ -90,12 +90,6 @@ Individual-level model output can be plotted using:
plot(opamod)
```
-To aid interpretation, individual PCCs and c-values can also be plotted relative to user-specified thresholds:
-
-```{r threshold_plots, fig.width=9, fig.height=4.5, fig.align="center"}
-plot(opamod, pcc_threshold = 90, cval_threshold = 0.1)
-```
-
### Pairwise comparison of measurement conditions
Pairwise comparisons of measurement conditions can be calculated by applying the `compare_conditions()` function to an `opafit` object produced by a call to `opa()`:
@@ -111,7 +105,7 @@ print(condition_comparisons)
If the data consist of multiple groups a categorical grouping variable can be passed with the `group` keyword to produce results for each group within the data, in addition to individual results.
```{r group_data}
-dat$group <- rep(c("A", "B", "C", "D"), 5)
+dat$group <- rep(c("A", "B", "C", "D"), each = 5)
dat$group <- factor(dat$group, levels = c("A", "B", "C", "D"))
opamod2 <- opa(dat[, 1:4], h, group = dat$group)
diff --git a/README.md b/README.md
index 7c07543..6105aa9 100644
--- a/README.md
+++ b/README.md
@@ -148,15 +148,6 @@ plot(opamod)
-To aid interpretation, individual PCCs and c-values can also be plotted
-relative to user-specified thresholds:
-
-``` r
-plot(opamod, pcc_threshold = 90, cval_threshold = 0.1)
-```
-
-
-
### Pairwise comparison of measurement conditions
Pairwise comparisons of measurement conditions can be calculated by
@@ -189,7 +180,7 @@ can be passed with the `group` keyword to produce results for each group
within the data, in addition to individual results.
``` r
-dat$group <- rep(c("A", "B", "C", "D"), 5)
+dat$group <- rep(c("A", "B", "C", "D"), each = 5)
dat$group <- factor(dat$group, levels = c("A", "B", "C", "D"))
opamod2 <- opa(dat[, 1:4], h, group = dat$group)
@@ -202,33 +193,33 @@ summary(opamod2, digits = 3)
#> Ordinal Pattern Analysis of 4 observations for 20 individuals in 4 groups
#>
#> Between subjects results:
-#> PCC cval
-#> A 100.000 <0.001
-#> B 86.667 <0.001
-#> C 93.333 <0.001
-#> D 93.333 <0.001
+#> PCC cval
+#> A 96.667 <0.001
+#> B 93.333 <0.001
+#> C 86.667 0.002
+#> D 96.667 <0.001
#>
#> Within subjects results:
#> Individual PCC cval
#> A 1 100.000 0.034
-#> A.1 5 100.000 0.035
-#> A.2 9 100.000 0.045
-#> A.3 13 100.000 0.044
-#> A.4 17 100.000 0.047
-#> B 2 100.000 0.053
-#> B.1 6 83.333 0.191
-#> B.2 10 83.333 0.165
-#> B.3 14 83.333 0.166
-#> B.4 18 83.333 0.159
-#> C 3 83.333 0.185
-#> C.1 7 100.000 0.044
-#> C.2 11 100.000 0.043
-#> C.3 15 83.333 0.158
-#> C.4 19 100.000 0.05
-#> D 4 100.000 0.055
-#> D.1 8 100.000 0.047
-#> D.2 12 66.667 0.379
-#> D.3 16 100.000 0.05
+#> A.1 2 100.000 0.035
+#> A.2 3 83.333 0.178
+#> A.3 4 100.000 0.044
+#> A.4 5 100.000 0.047
+#> B 6 83.333 0.18
+#> B.1 7 100.000 0.037
+#> B.2 8 100.000 0.048
+#> B.3 9 100.000 0.043
+#> B.4 10 83.333 0.158
+#> C 11 100.000 0.049
+#> C.1 12 66.667 0.392
+#> C.2 13 100.000 0.043
+#> C.3 14 83.333 0.158
+#> C.4 15 83.333 0.156
+#> D 16 100.000 0.055
+#> D.1 17 100.000 0.047
+#> D.2 18 83.333 0.158
+#> D.3 19 100.000 0.05
#> D.4 20 100.000 0.044
#>
#> PCCs were calculated for pairwise ordinal relationships using a difference threshold of 0.
@@ -261,10 +252,10 @@ 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
+#> Group 1 PCC: 96.66667
+#> Group 2 PCC: 93.33333
+#> PCC difference: 3.333333
+#> cval: 0.776
#> Comparison type: two-tailed
```
diff --git a/man/figures/README-plot_hypothesis-1.png b/man/figures/README-plot_hypothesis-1.png
index 3e3e670..5a6a4cc 100644
Binary files a/man/figures/README-plot_hypothesis-1.png and b/man/figures/README-plot_hypothesis-1.png differ
diff --git a/man/figures/README-plot_opamod1-1.png b/man/figures/README-plot_opamod1-1.png
index 009aaa7..0c23c3e 100644
Binary files a/man/figures/README-plot_opamod1-1.png and b/man/figures/README-plot_opamod1-1.png differ
diff --git a/man/figures/README-plot_opamod2-1.png b/man/figures/README-plot_opamod2-1.png
index 2fce582..611b74e 100644
Binary files a/man/figures/README-plot_opamod2-1.png and b/man/figures/README-plot_opamod2-1.png differ