recodeCheck: Change labeling of 'checkbox' variables

In redcapAPI: Interface to 'REDCap'

Change labeling of checkbox variables

Description

Rewrites the labeling of checkbox variables from Checked/Unchecked to Yes/No (or some other user specified labeling).

Usage

recodeCheck(
  df,
  vars,
  old = c("Unchecked", "Checked"),
  new = c("No", "Yes"),
  reverse = FALSE
)

Arguments

df	A data frame, presumably retrieved from REDCap, though not a strict requirement.
vars	Optional character vector of variables to convert. If left missing, all of the variables in df that are identified as checkbox variables are relabeled. See 'Details' for more about identifying checkbox variables.
old	A character vector to be passed to factor. This indicates the levels to be replaced and their order.
new	A character vector of labels to replace the values in levels. The first value becomes the reference value.
reverse	For convenience, if the user would prefer to reverse the order of the elements in levels and labels, simply set this to TRUE.

Details

checkbox variables are not identified using the metadata from the REDCap database. Instead, variables are scanned, and those variables in which every value is in levels are assumed to be checkbox variables.

Realistically, this could be used to relabel any set of factors with identical labels, regardless of the data source. The number of labels is not limited, but levels and labels should have the same length.

The actual code to perform this is not particularly difficult (df[checkbox] <- lapply(df[checkbox], factor, levels=levels, labels=labels)), but checkbox variables are common enough in REDCap (and the Checked/Unchecked scheme so unpalatable) that a quick way to replace the labels was highly desirable

redcapAPI documentation built on Sept. 13, 2023, 1:07 a.m.