Shiny-app

In REDCapCAST: REDCap Metadata Casting and Castellated Data Handling

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

To make the easiest possible transition from spreadsheet/dataset to REDCap, I have created a small app, which adds a graphical interface to the casting of a data dictionary and data upload. Install the package and launch the app as follows:

REDCapCAST::shiny_cast()

The app primarily wraps one function: ds2dd_detailed().

library(REDCapCAST)
ds <- REDCap_split(
    records = redcapcast_data,
    metadata = redcapcast_meta,
    forms = "all"
  ) |> 
  sanitize_split() |>
  redcap_wider() 
str(ds)

ds|> 
  ds2dd_detailed(metadata = names(REDCapCAST::redcapcast_meta))|>  
  purrr::pluck("data") |> 
  str()

ds|> 
  ds2dd_detailed(metadata = names(REDCapCAST::redcapcast_meta))|>  
  purrr::pluck("meta") |> 
  head(10)

Different data formats are accepted, which all mostly implements the readr::col_guess() functionality to parse column classes.

To ensure uniformity in data import this parsing has been implemented on its own to use with ds2dd_detailed() or any other data set for that matter:

ds_parsed <- redcapcast_data |> 
  dplyr::mutate(dplyr::across(dplyr::everything(),as.character)) |> 
  parse_data()
str(ds_parsed)

It will ignore specified columns, which is neat for numeric-looking strings like cpr-with a leading 0:

redcapcast_data |> 
  dplyr::mutate(dplyr::across(dplyr::everything(),as.character)) |> 
  parse_data(ignore.vars = c("record_id","cpr")) |> 
  str()

Column classes can be passed to parse_data().

Making a few crude assumption for factorising data, numchar2fct() factorises numerical and character vectors based on a set threshold for unique values:

mtcars |> str()
mtcars |>
  numchar2fct(numeric.threshold = 6) |>
  str()

ds_parsed|>
  numchar2fct(numeric.threshold = 2) |>
  str()

REDCapCAST documentation built on April 4, 2025, 3:18 a.m.