Transform skewed variables (aiming at they conform to a normal distribution) in .omv-files for the statistical spreadsheet 'jamovi' (https://www.jamovi.org)
Source:R/transform_vars_omv.R
transform_vars_omv.Rd
Transform skewed variables (aiming at they conform to a normal distribution) in .omv-files for the statistical spreadsheet 'jamovi' (https://www.jamovi.org)
Usage
transform_vars_omv(
dtaInp = NULL,
fleOut = "",
varXfm = NULL,
psvAnl = FALSE,
usePkg = c("foreign", "haven"),
selSet = "",
...
)
Arguments
- dtaInp
Either a data frame or the name of a data file to be read (including the path, if required; "FILENAME.ext"; default: NULL); files can be of any supported file type, see Details below
- fleOut
Name of the data file to be written (including the path, if required; "FILE_OUT.omv"; default: ""); if empty, the resulting data frame is returned instead
- varXfm
Named list variable where the name indicates which transformation is to be carried out and where each list entry points to one or more variables to be transformed using this transformation. See Details for more information.
- psvAnl
Whether analyses that are contained in the input file shall be transferred to the output file (default: FALSE)
- usePkg
Name of the package: "foreign" or "haven" that shall be used to read SPSS, Stata and SAS files; "foreign" is the default (it comes with base R), but "haven" is newer and more comprehensive
- selSet
Name of the data set that is to be selected from the workspace (only applies when reading .RData-files)
- ...
Additional arguments passed on to methods; see Details below
Value
a data frame (only returned if fleOut
is empty) where the order of variables / columns of the input data set is re-arranged
Details
varXfm
has to be a named list variable where the names can either indicate the type of transformation or the kind and degree of skewness that shall be corrected. For the type of transformation, the following names are valid:posSqr
,negSqr
,posLog
,negLog
,posInv
,negInv
; where the second part of the name indicates the transformation to be carried out:...Sqr
- square root,...Log
- logarithm to the basis 10,...Inv
- inversion, i.e., 1 / original value), and where the first part of the name indicates whether the original value is used (pos...
) or whether the original value is subtracted from the maximum value of that variable (neg...
; a constant of 1 is added to the maximum value for...Log
and...Inv
transformations). For the degree and kind of skewness, the following names are valid:mdrPos
,strPos
,svrPos
,mdrNeg
,strNeg
,svrNeg
(degree: moderate, strong, severe; kind: positive or negative).The ellipsis-parameter (
...
) can be used to submit arguments / parameters to the functions that are used for reading and writing the data. By clicking on the respective function under “See also”, you can get a more detailed overview over which parameters each of those functions take. The functions are:read_omv
andwrite_omv
(for jamovi-files),read.table
(for CSV / TSV files; using similar defaults asread.csv
for CSV andread.delim
for TSV which both are based uponread.table
),load
(for .RData-files),readRDS
(for .rds-files),read_sav
(needs the R-packagehaven
) orread.spss
(needs the R-packageforeign
) for SPSS-files,read_dta
(haven
) /read.dta
(foreign
) for Stata-files,read_sas
(haven
) for SAS-data-files, andread_xpt
(haven
) /read.xport
(foreign
) for SAS-transport-files. If you would like to usehaven
, you may need to install it usinginstall.packages("haven", dep = TRUE)
.
See also
transform_vars_omv
internally uses the following functions for reading and writing data files in different formats: read_omv()
and
write_omv()
for jamovi-files, utils::read.table()
for CSV / TSV files, load()
for reading .RData-files, readRDS()
for .rds-files,
haven::read_sav()
or foreign::read.spss()
for SPSS-files, haven::read_dta()
or foreign::read.dta()
for Stata-files, haven::read_sas()
for
SAS-data-files, and haven::read_xpt()
or foreign::read.xport()
for SAS-transport-files.
Examples
if (FALSE) { # \dontrun{
# generate skewed variables
set.seed(335)
dtaInp <- data.frame(MP = rnorm(1000) * 1e-1 + rexp(1000, 2) * (1 - 1e-1),
MN = rnorm(1000) * 1e-1 - rexp(1000, 2) * (1 - 1e-1),
SP = rnorm(1000) * 1e-2 + rexp(1000, 2) * (1 - 1e-2),
SN = rnorm(1000) * 1e-2 - rexp(1000, 2) * (1 - 1e-2),
EP = rnorm(1000) * 1e-4 + rexp(1000, 2) * (1 - 1e-4),
EN = rnorm(1000) * 1e-4 - rexp(1000, 2) * (1 - 1e-4))
jmv::descriptives(data = dtaInp, skew = TRUE, sw = TRUE)
crrXfm <- list(posSqr = c("MP"), negSqr = c("MN"), posLog = c("MP", "SP"), negLog = c("SN"),
posInv = c("MP", "SP", "EP"), negInv = c("EN"))
dtaOut <- jmvReadWrite::transform_vars_omv(dtaInp = dtaInp, varXfm = crrXfm)
jmv::descriptives(data = dtaOut, skew = TRUE, sw = TRUE)
crrXfm <- list(mdrPos = c("MP"), mdrNeg = c("MN"), strPos = c("SP"), strNeg = c("SN"),
svrPos = c("EP"), svrNeg = c("EN"))
dtaOut <- jmvReadWrite::transform_vars_omv(dtaInp = dtaInp, varXfm = crrXfm)
jmv::descriptives(data = dtaOut, skew = TRUE, sw = TRUE)
} # }