redcap_import_recode: REDCap Recode

In aghaynes/redcaptools: Tools for exporting and working with REDCap data

REDCap Recode

Description

This function loops through all the variables of a data set and compares them with the field type and validation of the variables as set up in REDCap.
The REDCap data dictionary can either be directly provided or downloaded from the REDCap project by providing an API token and matching URL.
Variables can be converted automatically or manually to match the type and validation in REDCap.
The script will then summarize all values that do not match the expected format and will look for values that could potentially indicate missing values (such as 'missing', 'excluded',...).
In a second step, these values can be recoded automatically or manually if missing data codes have defined in REDCap Additional Customizations (or simply set to NA).
If a variable has been converted to a factor (e.g., radio button field), the recoding is (additionally) prompted for all factor levels.
The function returns a data frame with the recoded variables, writes an overview csv-table, and the executed code to a txt-file for copy-pasting and adjusting/reusing.
It is advised to use redcap_import_select on the data first, before running this function.

Usage

redcap_import_recode(
  selected_data,
  dict = NULL,
  missing_codes = NULL,
  rc_token,
  rc_url,
  start_var = 1,
  pot_miss = c("miss", "unknown", "excluded", "^0$", "NA", "N.A."),
  if_empty = NA,
  auto_conv = TRUE,
  auto_recode = FALSE,
  auto_recode_precision = 0.5,
  skip_intro = FALSE,
  continue = TRUE,
  suppress_txt = FALSE,
  log = TRUE,
  log_code = "redcap_import_recode_code.txt",
  log_table = "redcap_import_recode_overview.csv",
  wait = 2,
  ...
)

Arguments

selected_data	Data to be recoded
dict	Data dictionary (e.g. as downloaded from REDCap or via redcap_export_meta(rc_token, rc_url)$meta). If not supplied, this will be downloaded from the API using rc_token and rc_token.
missing_codes	If a data dictionary is provided by the user, Missing Data Codes as defined in REDCap Additional Customizations can be provided here (if set up accordingly). The Missing Data Codes should be provided in a single string with [code] [label] separated by a comma and a pipe between the options (e.g., "-99, Missing | EXCL, Excluded | NA, not available"). If no data dictionary is provided, the codes will be downloaded from the API using rc_token and rc_token (if set up accordingly).
rc_token	REDCap API token
rc_url	Link to REDCap API
start_var	Define in which column of the data the loop should start. Default = 1.
pot_miss	The provided data is inspected for potential missing values that could be recoded. This is mainly helpful for text variables. Expressions can simply be defined in a character vector and a text-search is applied to search through the data. Default = c("miss","unknown","excluded","^0$","NA","N.A."). To disable this search set pot_miss to NULL.
if_empty	Sets a default value for empty cells. This value can be changed for each variable when using manual recoding. Default = NA (meaning the cell remains empty).
auto_conv	If TRUE, the variable will be auto-converted according to the best matching field type and validation in REDCap. If FALSE, the user can decide how the variable should be converted. If the option to continue is active (see below), this auto-conversion can be switched on and off while running the script. Default = TRUE.
auto_recode	If TRUE, the values that need recoding will be auto-recoded by matching them with codes and labels as set up in REDCap. If FALSE, the user can decide to recode the values as suggested or to recode each value individually. Default = FALSE.
auto_recode_precision	The values that need recoding are compared with codes and labels as set up in REDCap. With this numeric similarity index between 0 (no similarity at all = shows basically all code/labels as similar) and 1 (identical = shows only perfect codes/labels) the number of suggestions can be adjusted. If auto-recoding is switched off, this index can be adjusted while running the script. If multiple matches are found, the value will be set to NA. Default = 0.5.
skip_intro	If TRUE, the introduction messages will be skipped. Default = FALSE
continue	If TRUE, a question to continue will be asked before moving along the loop. Default = TRUE.
suppress_txt	If TRUE, all text output will be suppressed when used with auto-conversion and auto-recoding. This is not recommended and should only be used for testing. Default = FALSE.
log	If TRUE, an overview csv-table, and a txt-file are stored in the working directory. Default = TRUE.
log_code	Name and location of the txt-file containing the executed code. Default = redcap_import_recode_code.txt.
log_table	Name and location of the csv.table containing the tabular overview. Default = redcap_import_recode_overview.csv.
wait	Allows you to set the latency time between the steps. Default = 2s.
...	other parameters used for redcap_import_dates or redcap_import_times

Value

Data frame with recoded data. Log-file with executed code.

Examples

# data(importdemo_data)
# data(importdemo_dict)
# redcap_import_recode(importdemo_data, importdemo_dict)

# if using local data:
# token <- "xxxxx"
# url <- "xxxxx"
# file <- "data.csv"
# redcap_import_recode(file, rc_token = token, rc_url = url)

aghaynes/redcaptools documentation built on April 5, 2025, 9:28 a.m.