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Description

Helper Functions for Working with 'REDCap' Data.

Helper functions for processing 'REDCap' data in R. 'REDCap' is a web-enabled application for building and managing surveys and databases developed at Vanderbilt University.

CRAN status Lifecycle: maturing CRAN downloads

tidyREDCap

tidyREDCap is an R package with functions for processing REDCap data.

'REDCap' (Research Electronic Data CAPture; https://projectredcap.org) is a web-enabled application for building and managing surveys and databases developed at Vanderbilt University.

What tidyREDCap Functions Can Do for You?

Load All Data from REDCap into R with One Line of Code

  • 💥 NEW in Version 1.1 💥 import_instruments() includes the repeat number for repeated instruments/forms/questionnaires.

  • import_instruments() will use an API call to load every instrument/questionnaire into its own R dataset. If the REDCap project is longitudinal or has repeated instruments, the function will remove blank records.

Show the Field Labels Inside RStudio

  • After loading data into R using RStudio with the import_instruments() function, you can see both the variable name and the text that appears to users of REDCap. All you need to do is click on the dataset's name in the Environment tab or use the View() function. The column headings will include both the variable name and the Field Label from REDCap.

  • 💥 NEW in Version 1.1 💥 Functions coming from packages outside of tidyREDCap may not understand what to do with labeled variables. So, tidyREDCap includes a new drop_labels() function that will allow you to strip the labels before using functions that want unlabeled data.

Working with Choose One Questions

  • make_choose_one_table(): print a janitor::tabyl() style table with a variable label. This function lets you print one choice from a choose all that apply question.

Working with Choose All that Apply Questions

REDCap exports the responses to a choose all that apply question into many similarly named questions. tidyREDCap helps summarize the responses with two functions:

  • make_binary_word(): converts all the responses into a single descriptive "word"
  • make_choose_all_table(): converts all the responses into a single summary table

Working with Repeated Measures

Projects that have repeated assessments with different questionnaires/instruments export with holes in the CSV. tidyREDCap will parse the export and create tables for any of the questionnaires/instruments:

  • make_instrument(): makes a tibble for a questionnaire/instrument

What are the tidyREDCap Websites?

Main Page: https://raymondbalise.github.io/tidyREDCap/
User Guides: https://raymondbalise.github.io/tidyREDCap/articles/
Development Site: https://github.com/RaymondBalise/tidyREDCap

Where Can I Find tidyREDCap?

Offical Release

You can get the latest official release of tidyREDCap from CRAN.

install.packages("tidyREDCap")

Development Release

Run these two lines of code to install tidyREDCap from GitHub (this requires RTools for Windows or Xcode for Mac to be installed on your computer):

if (!requireNamespace("devtools")) install.packages("devtools")
devtools::install_github("RaymondBalise/tidyREDCap")

What is new on the development release?

  • 💥 NEW in Version 1.1.0.9000 💥 adds make_yes_no() function to convert "checked" or "yes"-like answers to "Yes" and other answers to "No or Unknown".
  • 💥 NEW in Version 1.1.0.9000 💥 adds make_yes_no_unknown() function to convert "checked" or "yes"-like answers to "Yes"", unchecked or "no"-like answers to "No" and other answers to "Unknown".

What if I Find a Problem?

We are currently in active development of tidyREDCap. If one of our functions does not work the way that you expect, or if one of our functions is broken, please submit an issue ticket (using a reproducible example) to our issues page. If you have a cool idea for our next new function, also submit an issue ticket. If you are an R developer and want so contribute to this package, please submit an issue ticket or a pull request.

Who Are Our Supporters?

The development of this package was supported by:

  • Healing Communities Study: Developing and Testing and Integrated Approach to Address the Opioid Crisis-New York State.
    • National Institute on Drug Abuse, 1 UM1 DA049415
  • CTN-0094 Individual Level Predictive Modeling of Opioid Use Disorder Treatment Outcome.
    • Florida Node Alliance Of The Drug Abuse Clinical Trials Network NIDA UG1 DA013720
  • University of Miami Center for HIV and Researching Mental Health (CHARM)
    • NIH 1P30MH116867-01A1
  • University of Miami, Sylvester Comprehensive Cancer Center
  • Florida International University, Stempel College of Public Health.
Metadata

Version

1.1.1

License

Unknown

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