clean_REDCap — clean_REDCap • thekidsbiostats

Clean a REDCap extract by applying factor levels and convert column classes per the REDCap data dictionary.

Usage

clean_REDCap(
  d,
  dict,
  numeric_date = FALSE,
  yesno_to_bool = FALSE,
  quiet = FALSE
)

Arguments

d: REDCap (data frame)
dict: REDCap data dictionary (data frame)
numeric_date: (default FALSE) set to TRUE if MS Excel has helpfully converted to a numeric date
yesno_to_bool: (default FALSE) convert factors with levels c("Yes", "No") to logical objects?
quiet: (default FALSE) pass quiet argument to lubridate functions

Value

cleaned data frame

Examples

if (FALSE) { # \dontrun{

dat <- tibble(var = c("0", "1"))

dictionary <- tibble(`Variable / Field Name` = "var",
  `Field Type` = "radio",
  `Field Label` = "Label",
  `Choices, Calculations, OR Slider Labels` = "0, No | 1, Yes",
  `Text Validation Type OR Show Slider Number` = NA)

(dat_clean <- clean_REDCap(dat, dictionary))

} # }