setupfile: Create setup files for SPSS, Stata, SAS and R

In DDIwR: DDI with R

Create setup files for SPSS, Stata, SAS and R

Description

Creates a setup file, based on a list of variable and value labels.

Usage

setupfile(
  obj,
  file = "",
  type = "all",
  csv = "",
  recode = TRUE,
  OS = "",
  stringnum = TRUE,
  ...
)

Arguments

obj	A data frame, or a list object containing the metadata, or a path to a data file or to a directory where such objects are located, for batch processing
file	Character, the (path to the) setup file to be created
type	The type of setup file, can be: "SPSS", "Stata", "SAS", "R", or "all" (default)
csv	The original dataset, used to create the setup file commands, or a path to the directory where the .csv files are located, for batch processing
recode	Logical, recode missing values to extended .a-.z range
OS	The target operating system, for the eol - end of line character(s)
stringnum	Logical, recode string variables to numeric
...	Other arguments, see Details below

Details

When a path to a metadata directory is specified for the argument obj, then next argument file is silently ignored and all created setup files are saved in a directory called "Setup Files" that (if not already found) is created in the working directory.

The argument file expects the name of the final setup file being saved on the disk. If not specified, the name of the object provided for the obj argument will be used as a filename.

If file is specified, the argument type is automatically determined from the file's extension, otherwise when type = "all", the function produces one setup file for each supported type.

If batch processing multiple files, the function will inspect all files in the provided directory, and retain only those with the extension .R or .r or DDI versions with the extension .xml or .XML (it will subsequently generate an error if the .R files do not contain an object list, or if the .xml files do not contain a DDI structured metadata file).

If the metadata directory contains a subdirectory called "data" or "Data", it will match the name of the metadata file with the name of the .csv file (their names have to be exactly the same, regardless of their extension).

The csv argument can provide a data frame object produced by reading the .csv file, or a path to the directory where the .csv files are located. If the user doesn't provide something for this argument, the function will check the existence of a subdirectory called data in the directory where the metadata files are located.

In batch mode, the code starts with the argument delim = ",", but if the .csv file is delimited differently it will also try hard to find other delimiters that will match the variable names in the metadata file. At the initial version 0.1-0, the automatically detected delimiters include ";" and "\t".

The argument OS (case insensitive) can be either:
"Windows" (default), or "Win",
"MacOS", "Darwin", "Apple", "Mac",
"Linux".

The end of line character(s) changes only when the target OS is different from the running OS.

Value

A setup file to complement the imported raw dataset.

Author(s)

Adrian Dusa

Examples

codebook <- list(dataDscr = list(
ID = list(
    label = "Questionnaire ID",
    type = "num",
    measurement = "interval"
),
V1 = list(
    label = "Label for the first variable",
    labels = c(
        "No"             =  0,
        "Yes"            =  1,
        "Not applicable" = -97,
        "Not answered"   = -99),
    na_values = c(-99, -97),
    type = "cat",
    measurement = "nominal"
),
V2 = list(
    label = "Label for the second variable",
    labels = c(
        "Very little"    =  1,
        "Little"         =  2,
        "So, so"         =  3,
        "Much"           =  4,
        "Very much"      =  5,
        "Don't know"     = -98),
    na_values = c(-98),
    type = "cat",
    measurement = "ordinal"
),
V3 = list(
    label = "Label for the third variable",
    labels = c(
        "First answer"   = "A",
        "Second answer"  = "B",
        "Don't know"     = -98),
    na_values = c(-98),
    type = "cat",
    measurement = "nominal"
),
V4 = list(
    label = "Number of children",
    labels = c(
        "Don't know"     = -98,
        "Not answered"   = -99),
    na_values = c(-99, -98),
    type = "numcat",
    measurement = "ratio"
)))


## Not run: 
# IMPORTANT:
# make sure to set the working directory to a directory with
# read/write permissions
# setwd("/path/to/read/write/directory")


setupfile(codebook)


# if the csv data file is available
setupfile(codebook, csv="/path/to/csv/file.csv")


# generating a specific type of setup file
setupfile(codebook, file = "codebook.do") # type = "Stata" also works


# other types of possible utilizations, using paths to specific files
# an XML file containing a DDI metadata object

setupfile("/path/to/the/metadata/file.xml", csv="/path/to/csv/file.csv")


# or in batch mode, specifying entire directories
setupfile("/path/to/the/metadata/directory", csv="/path/to/csv/directory")

## End(Not run)

DDIwR documentation built on Oct. 1, 2023, 5:06 p.m.