% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/redcap_wider.R
\name{redcap_wider}
\alias{redcap_wider}
\title{Transforms list of REDCap data.frames to a single wide data.frame}
\usage{
redcap_wider(
  data,
  event.glue = "{.value}____{redcap_event_name}",
  inst.glue = "{.value}____{redcap_repeat_instance}"
)
}
\arguments{
\item{data}{A list of data frames}

\item{event.glue}{A \link[glue]{glue} string for repeated events naming}

\item{inst.glue}{A \link[glue]{glue} string for repeated instruments naming}
}
\value{
data.frame in wide format
}
\description{
Converts a list of REDCap data.frames from long to wide format.
In essence it is a wrapper for the \link[tidyr]{pivot_wider} function applied
on a REDCap output (from \link[REDCapCAST]{read_redcap_tables}) or manually
split by \link[REDCapCAST]{REDCap_split}.
}
\examples{
# Longitudinal
list1 <- list(
  data.frame(
    record_id = c(1, 2, 1, 2),
    redcap_event_name = c("baseline", "baseline", "followup", "followup"),
    age = c(25, 26, 27, 28)
  ),
  data.frame(
    record_id = c(1, 2),
    redcap_event_name = c("baseline", "baseline"),
    gender = c("male", "female")
  )
)
redcap_wider(list1)
# Simpel with two instruments
list2 <- list(
  data.frame(
    record_id = c(1, 2),
    age = c(25, 26)
  ),
  data.frame(
    record_id = c(1, 2),
    gender = c("male", "female")
  )
)
redcap_wider(list2)
# Simple with single instrument
list3 <- list(data.frame(
  record_id = c(1, 2),
  age = c(25, 26)
))
redcap_wider(list3)
# Longitudinal with repeatable instruments
list4 <- list(
  data.frame(
    record_id = c(1, 2, 1, 2),
    redcap_event_name = c("baseline", "baseline", "followup", "followup"),
    age = c(25, 26, 27, 28)
  ),
  data.frame(
    record_id = c(1, 1, 1, 1, 2, 2, 2, 2),
    redcap_event_name = c(
      "baseline", "baseline", "followup", "followup",
      "baseline", "baseline", "followup", "followup"
    ),
    redcap_repeat_instrument = "walk",
    redcap_repeat_instance = c(1, 2, 1, 2, 1, 2, 1, 2),
    dist = c(40, 32, 25, 33, 28, 24, 23, 36)
  ),
  data.frame(
    record_id = c(1, 2),
    redcap_event_name = c("baseline", "baseline"),
    gender = c("male", "female")
  )
)
redcap_wider(list4)
}