Merge pull request #209 from CHOP-CGTInformatics/cran-1.2-prep

CRAN 1.2 Prep

R/checks.R

@@ -745,7 +745,7 @@ check_fields_are_checkboxes <- function(metadata_tbl, call = caller_env()) {
 #' @title Check equal distinct values between two columns
 #'
 #' @description
-#' Takes a dataframe and two columns and checks if [n_distinct()] of the second
+#' Takes a dataframe and two columns and checks if `n_distinct` of the second
 #' column is all unique based on grouping of the first column.
 #'
 #' @param data a dataframe
@@ -757,8 +757,8 @@ check_fields_are_checkboxes <- function(metadata_tbl, call = caller_env()) {
 check_equal_col_summaries <- function(data, col1, col2, call = caller_env()) {
   summary <- data %>%
     summarise(
-      .by = {{ col1 }},
-      n = n_distinct({{ col2 }})
+      .by = col1,
+      n = n_distinct(col2)
     )
 
   total_n <- summary %>%

R/combine_checkboxes.R

@@ -19,8 +19,7 @@
 #'
 #' @param supertbl A supertibble generated by [read_redcap()]. Required.
 #' @param tbl The `redcap_form_name` of the data tibble to extract. Required.
-#' @param cols <[`tidy-select`][tidyr_tidy_select]> Checkbox columns to combine to
-#' single column. Required.
+#' @param cols Checkbox columns to combine to single column. Required.
 #' @param names_prefix String added to the start of every variable name.
 #' @param names_sep String to separate new column names from `names_prefix`.
 #' @param names_glue Instead of `names_sep` and `names_prefix`, you can supply
@@ -192,23 +191,26 @@ get_metadata_spec <- function(metadata_tbl,
   if (!is.null(names_glue)) {
     # Similar to pivot_*, use of `names_glue` overrides use of names_prefix/sep
     glue_env <- out %>%
-      select(.data$.value) %>%
-      mutate(.new_value = as.character(glue::glue_data(., names_glue))) %>% # nolint: object_usage_linter
+      select(.data$.value)
+
+    glue_env$.new_value <- as.character(glue::glue_data(glue_env, names_glue))
+
+    glue_env <- glue_env %>%
       select(.data$.new_value)
 
     out <- cbind(out, glue_env)
   } else {
     out <- out %>%
       mutate(
-        .new_value = case_when(names_prefix != "" ~ paste(names_prefix, .value, sep = names_sep),
+        .new_value = case_when(names_prefix != "" ~ paste(names_prefix, .data$.value, sep = names_sep),
           .default = paste(names_prefix, .data$.value, sep = "")
         )
       )
   }
 
   # Check that for each unique value of .value there is one unique value of .new_value
   # May be removed in the future
-  check_equal_col_summaries(out, .value, .new_value) # nolint: object_usage_linter
+  check_equal_col_summaries(out, ".value", ".new_value") # nolint: object_usage_linter
 
   # Make sure selection is checkbox metadata field type
   check_fields_are_checkboxes(out)
@@ -257,11 +259,11 @@ replace_true <- function(col, col_name, metadata, raw_or_label) {
 #' based on the overall data tibble cross referenced with a nested section of the
 #' metadata tibble.
 #'
-#' [case_when()] logic helps determine whether the value is a coalesced singular
+#' `case_when` logic helps determine whether the value is a coalesced singular
 #' value or a user-specified one via `multi_value_label` or `values_fill`.
 #'
 #' @details
-#' This function is used in conjunction with [pmap()].
+#' This function is used in conjunction with `pmap()`.
 #'
 #' @keywords internal
 #'

R/read_redcap.R

@@ -260,17 +260,24 @@ read_redcap <- function(redcap_uri,
     db_data <- multi_choice_to_labels(db_data, db_metadata, raw_or_label)
   }
 
-  # Longitudinal Arms Check and Cleaning Application ----
-  # Check if database supplied is longitudinal to determine appropriate function
-  # to use
-  is_longitudinal <- if ("redcap_event_name" %in% names(db_data)) {
-    TRUE
+  # Database structure checks and definitions ----
+  is_longitudinal <- "redcap_event_name" %in% names(db_data)
+  has_repeating_structure <- "redcap_repeat_instance" %in% names(db_data)
+  has_repeating_events <- if (is_longitudinal && has_repeating_structure) {
+    any(
+      is.na(db_data$redcap_repeat_instrument) &
+        !is.na(db_data$redcap_repeat_instance)
+    )
   } else {
     FALSE
   }
 
   if (is_longitudinal) {
-    repeat_event_types <- get_repeat_event_types(db_data)
+    repeat_event_types <- if (has_repeating_events) {
+      get_repeat_event_types(db_data)
+    } else {
+      NULL
+    }
 
     linked_arms <- link_arms(
       redcap_uri = redcap_uri,
@@ -453,11 +460,17 @@ add_metadata <- function(supertbl, db_metadata, redcap_uri, token, suppress_redc
 #' @keywords internal
 
 add_event_mapping <- function(supertbl, linked_arms, repeat_event_types) {
-  event_info <- linked_arms %>%
-    left_join(repeat_event_types, by = c("unique_event_name" = "redcap_event_name")) %>%
+  event_info <- linked_arms
+
+  if (!is.null(repeat_event_types)) {
+    event_info <- event_info %>%
+      left_join(repeat_event_types, by = c("unique_event_name" = "redcap_event_name"))
+  }
+
+  event_info <- event_info %>%
     add_partial_keys(.data$unique_event_name) %>%
     select(
-      redcap_form_name = "form", "redcap_event", "event_name", "redcap_arm", "arm_name", "repeat_type"
+      redcap_form_name = "form", "redcap_event", "event_name", "redcap_arm", "arm_name", any_of("repeat_type")
     ) %>%
     nest(redcap_events = !"redcap_form_name")
 

README.Rmd

@@ -25,7 +25,7 @@ knitr::opts_chunk$set(
 [![OpenSSF Best Practices](https://bestpractices.coreinfrastructure.org/projects/6845/badge)](https://bestpractices.coreinfrastructure.org/projects/6845)
 <!-- badges: end -->
 
-The REDCapTidieR package provides an elegant way to [import](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#import) data from a [REDCap](https://www.project-redcap.org/) [project](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#project) into an R environment. It builds upon the [REDCapR](https://ouhscbbmc.github.io/REDCapR/) package to query the [REDCap API](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#redcap-api) and then transforms the returned data into a set of [tidy](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#tidy) [tibbles](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#tibble).
+The REDCapTidieR package provides an elegant way to [import](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#import) data from a [REDCap](https://projectredcap.org/) [project](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#project) into an R environment. It builds upon the [REDCapR](https://ouhscbbmc.github.io/REDCapR/) package to query the [REDCap API](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#redcap-api) and then transforms the returned data into a set of [tidy](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#tidy) [tibbles](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#tibble).
 
 REDCapTidieR is especially useful for dealing with complex REDCap projects that are [longitudinal](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#longitudinal-project) or include [repeating](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#repeating) [instruments](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#instrument) or both.
 

README.md

@@ -16,12 +16,11 @@ status](https://www.r-pkg.org/badges/version/REDCapTidieR)](https://CRAN.R-proje
 coverage](https://codecov.io/gh/CHOP-CGTInformatics/REDCapTidieR/branch/main/graph/badge.svg)](https://app.codecov.io/gh/CHOP-CGTInformatics/REDCapTidieR?branch=main)
 [![OpenSSF Best
 Practices](https://bestpractices.coreinfrastructure.org/projects/6845/badge)](https://bestpractices.coreinfrastructure.org/projects/6845)
-[![DOI](https://joss.theoj.org/papers/10.21105/joss.06277/status.svg)](https://doi.org/10.21105/joss.06277)
 <!-- badges: end -->
 
 The REDCapTidieR package provides an elegant way to
 [import](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#import)
-data from a [REDCap](https://www.project-redcap.org/)
+data from a [REDCap](https://projectredcap.org/)
 [project](https://chop-cgtinformatics.github.io/REDCapTidieR/articles/glossary.html#project)
 into an R environment. It builds upon the
 [REDCapR](https://ouhscbbmc.github.io/REDCapR/) package to query the

cran-comments.md

@@ -2,41 +2,27 @@
 
 Thank you for taking the time to review this submission and please reach out to either Stephan Kadauke, Richard Hanna, or Ezra Porter for any questions, comments, or concerns.
 
-This submission patches version 1.1.0 to fix a test failure introduced by an upcoming release of `labelled` 2.13.0. We have worked with the developer of `labelled` to ensure this patch resolves their reverse dependency check failures.
+This submission for v1.2.0 adds new functionality, new documentation, and patches several minor bugs.
 
 ## New Features
 
-There are no significant user-facing changes in this release.
-
-`read_redcap(raw_or_label = "haven")` now correctly casts categorical data values to character when their type is not character or numeric. This is a constraint of labels from the `haven` package which `labelled` will be checking for explicitly in their new release.
+The only new feature in this release is an analytics function that exists in a silo away from the rest of the core package.
 
 ## Test environments
 
-1. Local macOS Ventura 13.6.5, R 4.2.4
-2. R-hub
-    1. [Ubuntu 22.04.4 LTS, R-next, GCC](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/8650642187/job/23719620675)
-    2. [Ubuntu 22.04.4 LTS, R-release, GCC](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/8650642187/job/23719621223)
-    3. [Ubuntu 22.04.4 LTS, R-devel, GCC](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/8650642187/job/23719620358)
-    4. [Windows Server](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/8650642187/job/23719620965)
-3.  [win-builder](https://win-builder.r-project.org/V4B5Ar22pIf5/), development version.
-4.  [GiHub Actions](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions), Ubuntu 20.04.02 LTS
+1.  Local macOS Sonoma 14.6.1, R 4.4.0
+2.  R-hub
+    1.  [Ubuntu 22.04.5 LTS, R-next, GCC](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/11486785018/job/31969845126)
+    2.  [Ubuntu 22.04.5 LTS, R-release, GCC](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/11486785018/job/31969845814)
+    3.  [Ubuntu 22.04.4 LTS, R-devel, GCC](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/11486785018/job/31969845504)
+    4.  [Microsoft Windows Server 2022, 10.0.20348](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/11486785018/job/31969846106)
+3.  [win-builder](https://win-builder.r-project.org/OQCea7cbW815/), development version.
+4.  [GiHub Actions](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions), Ubuntu 20.04.05 LTS
 
 ## R CMD check results:
 
-- 0 ERRORs or WARNINGs on any builds
-
-- A NOTE is generated in win-builder resulting from the package maintainer email address changing relative to the last CRAN release. This is an artifact of a different email address than the package maintainer's being used for the submission to win-builder.
-
-```
-* checking CRAN incoming feasibility ... [14s] NOTE
-Maintainer: 'Richard Hanna <porterej@chop.edu>'
-
-New maintainer:
-  Richard Hanna <porterej@chop.edu>
-Old maintainer(s):
-  Richard Hanna <richardshanna91@gmail.com>
-```
+-   0 ERRORs or WARNINGs on any builds
 
 ## Downstream Dependencies:
 
-No downstream packages are affected. No packages depend/import/suggest REDCapTidieR. Results: <https://github.com/CHOP-CGTInformatics/REDCapTidieR/blob/main/revdep/cran.md>
+All packages that depend/import/suggest REDCapTidieR pass the [Reverse dependency checks](https://github.com/CHOP-CGTInformatics/REDCapTidieR/actions/runs/11486797194).

inst/WORDLIST

@@ -17,8 +17,10 @@ REDCapTidieR's
 RStudio
 Recode
 Recoding
+Stata
 Supertibble
 Supertibbles
+TRUEs
 Tibble
 Tibble's
 Tibbles
@@ -30,6 +32,7 @@ analytics
 api
 appendings
 cli
+de
 dplyr
 dropdown
 edu
@@ -38,6 +41,7 @@ ggplot
 gtsummary
 https
 httptest
+interpretable
 labelled
 multiselection
 nonrepeat
@@ -48,12 +52,15 @@ preprocess
 recode
 recoded
 recodes
+recoding
 skimr
 summarise
 supertbl
 supertibble
 supertibble's
+supertibbles
 tableStyleLight
+tbl
 tibble
 tibble's
 tibbles
@@ -62,7 +69,6 @@ tidyverse
 truefalse
 undirected
 unlabelled
-wb
 xlsx
 yesno
 ︎

paper/paper.bib

@@ -54,7 +54,7 @@ @Manual{redcapr_cit
   author = {Will Beasley},
   year = {2023},
   url = {https://ouhscbbmc.github.io/REDCapR/},
-  note = {https://ouhscbbmc.github.io/REDCapR/, https://github.com/OuhscBbmc/REDCapR, https://www.ouhsc.edu/bbmc/, https://project-redcap.org},
+  note = {https://ouhscbbmc.github.io/REDCapR/, https://github.com/OuhscBbmc/REDCapR, https://www.ouhsc.edu/bbmc/, https://projectredcap.org},
 }
 
 @Manual{redcapapi_cit,

paper/paper.html

@@ -381,7 +381,7 @@ <h4 class="date">XX November 2023</h4>
 <div id="summary" class="section level1">
 <h1>Summary</h1>
 <p>Capturing and storing electronic data is integral in the research
-world. <a href="https://www.project-redcap.org/">REDCap</a> <span class="citation">(Harris et al. 2009, 2019)</span> offers a secure web
+world. <a href="https://projectredcap.org/">REDCap</a> <span class="citation">(Harris et al. 2009, 2019)</span> offers a secure web
 application that lets users build databases and surveys with a robust
 front-end interface that can support data of any type, including data
 requiring compliance with standards for protected information.</p>

paper/paper.md

@@ -48,7 +48,7 @@ bibliography: paper.bib
 
 # Summary
 
-Capturing and storing electronic data is integral in the research world. [REDCap](https://www.project-redcap.org/) [@Harris2009; @Harris2019] offers a secure web application that lets users build databases and surveys with a robust front-end interface that can support data of any type, including data requiring compliance with standards for protected information.
+Capturing and storing electronic data is integral in the research world. [REDCap](https://projectredcap.org/) [@Harris2009; @Harris2019] offers a secure web application that lets users build databases and surveys with a robust front-end interface that can support data of any type, including data requiring compliance with standards for protected information.
 
 Many REDCap users use the R programming language [@r_cit] to extract and analyze their data. The [`REDCapR`](https://cran.r-project.org/web/packages/REDCapR/index.html) [@redcapr_cit] and [`redcapAPI`](https://cran.r-project.org/web/packages/redcapAPI/index.html) [@redcapapi_cit] packages allow R users to extract data directly into their programming environment. While this works well for simple REDCap databases, it becomes cumbersome for complex databases, because the REDCap API outputs a "block matrix"--a single table with varied granularity levels, which conflicts with the "tidy data" framework [@Wickham2014] that advocates for standardized data organization.