REDCapCAST/man/REDCap_split.Rd

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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/REDCap_split.r
\name{REDCap_split}
\alias{REDCap_split}
\title{Split REDCap repeating instruments table into multiple tables}
\usage{
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REDCap_split(
records,
metadata,
primary_table_name = "",
forms = c("repeating", "all")
)
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}
\arguments{
\item{records}{Exported project records. May be a \code{data.frame},
\code{response}, or \code{character} vector containing JSON from an API
call.}
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\item{metadata}{Project metadata (the data dictionary). May be a
\code{data.frame}, \code{response}, or \code{character} vector containing
JSON from an API call.}
\item{primary_table_name}{Name given to the list element for the primary
output table (as described in \emph{README.md}). Ignored if
\code{forms = 'all'}.}
\item{forms}{Indicate whether to create separate tables for repeating
instruments only or for all forms.}
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}
\value{
A list of \code{"data.frame"}s. The number of tables will differ
depending on the \code{forms} option selected.
\itemize{
\item \code{'repeating'}: one base table and one or more
tables for each repeating instrument.
\item \code{'all'}: a data.frame for each instrument, regardless of
whether it is a repeating instrument or not.
}
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}
\description{
This will take output from a REDCap export and split it into a base table
and child tables for each repeating instrument. Metadata
is used to determine which fields should be included in each resultant table.
}
\examples{
\dontrun{
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# Using an API call -------------------------------------------------------
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library(RCurl)
# Get the records
records <- postForm(
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uri = api_url, # Supply your site-specific URI
token = api_token, # Supply your own API token
content = 'record',
format = 'json',
returnFormat = 'json'
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)
# Get the metadata
metadata <- postForm(
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uri = api_url, # Supply your site-specific URI
token = api_token, # Supply your own API token
content = 'metadata',
format = 'json'
)
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# Convert exported JSON strings into a list of data.frames
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REDCapRITS::REDCap_split(records, metadata)
# Using a raw data export -------------------------------------------------
# Get the records
records <- read.csv("/path/to/data/ExampleProject_DATA_2018-06-03_1700.csv")
# Get the metadata
metadata <- read.csv("/path/to/data/ExampleProject_DataDictionary_2018-06-03.csv")
# Split the tables
REDCapRITS::REDCap_split(records, metadata)
# In conjunction with the R export script ---------------------------------
# You must set the working directory first since the REDCap data export script
# contains relative file references.
setwd("/path/to/data/")
# Run the data export script supplied by REDCap.
# This will create a data.frame of your records called 'data'
source("ExampleProject_R_2018-06-03_1700.r")
# Get the metadata
metadata <- read.csv("ExampleProject_DataDictionary_2018-06-03.csv")
# Split the tables
REDCapRITS::REDCap_split(data, metadata)
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}
}
\author{
Paul W. Egeler, M.S., GStat
}