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Closes #40 Initial ADCOEQ vignette #53

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Thank you for your Pull Request! We have developed this task checklist from the Development Process Guide to help with the final steps of the process. Completing the below tasks helps to ensure our reviewers can maximize their time on your code as well as making sure the admiral family codebase remains robust and consistent.

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@kathrinflunkert kathrinflunkert self-assigned this Nov 13, 2024
@kathrinflunkert kathrinflunkert linked an issue Nov 13, 2024 that may be closed by this pull request
Vignette: CoEQ ADaM (ADCOEQ?) #40
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Package Line Rate Health
admiralmetabolic 90% ✔
Summary 90% (156 / 173) ✔

@manciniedoardo
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manciniedoardo commented Nov 14, 2024 •
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Thanks for this! Some preliminary notes before review (feel free to ignore if still developing):

  • You'll need to add an entry in _pkgdown.yml so the vignette appears in the navigation bar.
  • Title is quite long, what about: Creating a Control of Eating Questionnaire ADaM
  • I would make the license text even more prominent - perhaps a "License" section right above the introduction.
  • In the intro section, please reference the Questionnaire ADaM vignette (see how ADVS template did it)
  • Ensure "admiralmetabolic" is inside curly brackets and backticks ({admiralmetabolic}) throughout for correct linkage.
  • Ensure "pharmaverse", dataset names and variables are also in backticks - see ADVS vignette.
  • tibble shouldn't be a required package as you use it only for internal examples
  • After "Required Packages", add "Programming Workflow" section - same as ADVS vignette. In general try follow ADVS vignette layout for consistency across the package.
  • For Read In Data section, mimic ADVS vignette there too - show any code for qs and dm/adsl
  • For unscheduled visits, is this approach likely to vary across studies? Should we specfiy this?
  • Not sure baseline and change from baseline sections are needed. Can we just reference admiral documentation?

And the most complex comment:

  • Can you leverage call_derivation() to make the code in the "scales and scores" section more efficient. I give an example below for two parameters and then you can generalise:
adcoeq3 <- adcoeq2 %>%
  call_derivation(
    derivation = derive_summary_records,
    variable_params = list(
      params(
        filter_add = (PARAMCD %in% c('COEQ09','COEQ10','COEQ11','COEQ12','COEQ19')),
        set_values_to = exprs(
          AVAL = mean(AVAL, na.rm = TRUE),
          PARAMCD = "COEQCRCO",
          PARAM = "COEQ - Craving Control"
      ),
      params(
        filter_add = (PARAMCD %in% c('COEQ03','COEQ13','COEQ14','COEQ15')),
         set_values_to = exprs(
           AVAL = mean(AVAL, na.rm = TRUE),
           PARAMCD = "COEQCRSW",
           PARAM = "COEQ - Craving for Sweet"
       )
    ),
    dataset_add = . ,
    by_vars = exprs(STUDYID, USUBJID, AVISIT, AVISITN, ADT, ADY, PARCAT1, TRTSDT, TRTEDT, TRT01P, TRT01A)

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@AndersAskeland AndersAskeland Awaiting requested review from AndersAskeland

@Sonali-netizen Sonali-netizen Awaiting requested review from Sonali-netizen

@manciniedoardo manciniedoardo Awaiting requested review from manciniedoardo

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Vignette: CoEQ ADaM (ADCOEQ?)
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@kathrinflunkert @manciniedoardo