Merge pull request #170 from CHOP-CGTInformatics/joss-feedback-1

JOSS Feedback Round 1

paper/paper.bib

@@ -59,11 +59,11 @@ @Manual{redcapr_cit
 
 @Manual{redcapapi_cit,
   title = {{redcapAPI}: Accessing data from REDCap projects using the API},
-  author = {Benjamin Nutter and Stephen Lane},
-  year = {2023},
-  doi = {10.5281/zenodo.11826},
-  note = {R package version 2.8.0},
-  url = {https://github.com/nutterb/redcapAPI/wiki},
+  author = {Shawn Garbett and Benjamin Nutter and Stephen Lane and Will Beasley and Jeffrey Horner and Jeremy Stephens and Marcus Lehr and Cole Beck and Savannah Obregon},
+  year = {2024},
+  doi = {10.5281/zenodo.10564837},
+  note = {R package version 2.8.3},
+  url = {https://github.com/vubiostat/redcapAPI},
 }
 
 @Manual{redcapdm_cit,

paper/paper.md

@@ -62,7 +62,7 @@ As of 2023, the REDCap Consortium boasts nearly 3 million users across over 150
 
 REDCap databases that contain repeating events and instruments require significant manual pre-processing, a major pain point for researchers and analysts. This is because the REDCap API returns a single table (Figure 1) that includes data from instruments that record data at different levels of granularity.
 
-While there are a few existing REDCap tools (Table 1), `REDCapTidieR` occupies a unique space by providing analysts with a framework returns a tidy data structure regardless of the size or complexity of the extracted database. Although some of these tools also offer functions for data processing, such as the [`tidyREDCap`](https://raymondbalise.github.io/tidyREDCap/) [@tidyredcap_cit] and [`REDCapDM`](https://ubidi.github.io/REDCapDM/index.html) [@redcapdm_cit] packages, only `REDCapTidieR` restructures the block matrix into an easy to use format.
+While several existing REDCap packages are available (Table 1), `REDCapTidieR` distinguishes itself by offering analysts a unique framework that returns a tidy data structure regardless of the size or complexity of the extracted database. Packages such as [`tidyREDCap`](https://raymondbalise.github.io/tidyREDCap/) [@tidyredcap_cit] and [`REDCapDM`](https://ubidi.github.io/REDCapDM/index.html) [@redcapdm_cit] also offer tools for data processing, while `redcapAPI` gives a wealth of options for data export in addition to features that break apart the block matrix using a base R framework. However, only `REDCapTidieR` deconstructs the block matrix into easily joinable tidy tables that form their own composite primary keys to preserve the relationships between each other in accordance with their unique granularity.
 
 `REDCapTidieR` is built with production readiness in mind. In addition to an extensive 98% coverage test suite, `REDCapTidieR` execution is evaluated against 15 test databases that cover many complex configuration scenarios. It also provides ample documentation through a `pkgdown` [site](https://chop-cgtinformatics.github.io/REDCapTidieR/index.html) [@redcaptidier_pkgdown_cit]. It is also built on top of `REDCapR`, which contains its own extensive test suite, and evaluated against an additional 26 test databases. `REDCapTidieR` meets the rigorous requirements of the [OpenSSF Best Practices Badge](https://www.bestpractices.dev/en/projects/6845) [@openssf_cit], which certifies open-source projects that adhere to criteria for delivering high-quality, robust, and secure software.
 
@@ -78,7 +78,7 @@ Table 1: Comparative breakdown of the landscape for REDCap tools in R.
 
 # Design
 
-The `REDCapTidieR::read_redcap()` function leverages `REDCapR` to make API calls to query the data and metadata of a REDCap project and returns the supertibble (Figure 1). The supertibble, named after the [`tibble` package](https://tibble.tidyverse.org/) [@tibble_cit], is an alternative presentation of the data in which multiple tables are linked together in a single object in a fashion consistent with tidy data principles.
+The `REDCapTidieR::read_redcap()` function leverages `REDCapR` to make API calls to query the data and metadata of a REDCap project and returns the supertibble (Figure 1). The supertibble, named after the [`tibble` package](https://tibble.tidyverse.org/) [@tibble_cit], is an alternative presentation of the data in which multiple tables are linked together in a single object in a fashion consistent with tidy data principles. Specific data tibbles within the supertibble, representing the data of individual REDCap instruments, can be easily joined using their composite primary keys.
 
 ![The REDCapTidieR Supertibble](images/Figure1.png)
 
@@ -94,7 +94,7 @@ Figure 1: The REDCapTidieR supertibble shown in the Data Viewer of the RStudio I
 
 # Acknowledgements
 
-We would like to thank Will Beasley, Paul Wildenhain, and Jan Marvin for their feedback and support in development.
+We would like to thank Jan Marvin and Raymond Balise for their feedback and support in development.
 
 This package was developed by the [Cell and Gene Therapy Informatics Team](https://www.chop.edu/centers-programs/cell-and-gene-therapy-informatics-team/our-team) of the [Children’s Hospital of Philadelphia](https://www.chop.edu).
 

renv.lock

@@ -281,14 +281,14 @@
     },
     "cli": {
       "Package": "cli",
-      "Version": "3.6.1",
+      "Version": "3.6.2",
       "Source": "Repository",
       "Repository": "CRAN",
       "Requirements": [
         "R",
         "utils"
       ],
-      "Hash": "89e6d8219950eac806ae0c489052048a"
+      "Hash": "1216ac65ac55ec0058a6f75d7ca0fd52"
     },
     "clipr": {
       "Package": "clipr",
@@ -942,7 +942,7 @@
     },
     "knitr": {
       "Package": "knitr",
-      "Version": "1.44",
+      "Version": "1.45",
       "Source": "Repository",
       "Repository": "CRAN",
       "Requirements": [
@@ -954,7 +954,7 @@
         "xfun",
         "yaml"
       ],
-      "Hash": "60885b9f746c9dfaef110d070b5f7dc0"
+      "Hash": "1ec462871063897135c1bcbe0fc8f07d"
     },
     "labelled": {
       "Package": "labelled",
@@ -1519,14 +1519,14 @@
     },
     "rlang": {
       "Package": "rlang",
-      "Version": "1.1.1",
+      "Version": "1.1.3",
       "Source": "Repository",
       "Repository": "CRAN",
       "Requirements": [
         "R",
         "utils"
       ],
-      "Hash": "a85c767b55f0bf9b7ad16c6d7baee5bb"
+      "Hash": "42548638fae05fd9a9b5f3f437fbbbe2"
     },
     "rmarkdown": {
       "Package": "rmarkdown",
@@ -1717,22 +1717,22 @@
     },
     "stringi": {
       "Package": "stringi",
-      "Version": "1.7.12",
+      "Version": "1.8.3",
       "Source": "Repository",
-      "Repository": "CRAN",
+      "Repository": "RSPM",
       "Requirements": [
         "R",
         "stats",
         "tools",
         "utils"
       ],
-      "Hash": "ca8bd84263c77310739d2cf64d84d7c9"
+      "Hash": "058aebddea264f4c99401515182e656a"
     },
     "stringr": {
       "Package": "stringr",
-      "Version": "1.5.0",
+      "Version": "1.5.1",
       "Source": "Repository",
-      "Repository": "CRAN",
+      "Repository": "RSPM",
       "Requirements": [
         "R",
         "cli",
@@ -1743,7 +1743,7 @@
         "stringi",
         "vctrs"
       ],
-      "Hash": "671a4d384ae9d32fc47a14e98bfa3dc8"
+      "Hash": "960e2ae9e09656611e0b8214ad543207"
     },
     "styler": {
       "Package": "styler",

tests/testthat/test-write.R

@@ -339,6 +339,7 @@ test_that("bind_supertbl_metadata works", {
 
 test_that("Combining skimr, labelled, and xlsx returns expected snapshot", {
   skip_on_cran()
+  skip_on_ci()
   out <-
     read_redcap(Sys.getenv("REDCAP_URI"), Sys.getenv("REDCAPTIDIER_CLASSIC_API")) %>%
     # Suppress expected warnings from the REDCapTidieR Classic database.