| Name : R-normalr
| |
| Version : 1.0.0
| Vendor : obs://build_opensuse_org/devel:languages:R
|
| Release : lp153.13.2
| Date : 2024-06-14 11:54:30
|
| Group : Development/Libraries/Other
| Source RPM : R-normalr-1.0.0-lp153.13.2.src.rpm
|
| Size : 0.04 MB
| |
| Packager : (none)
| |
| Summary : Normalisation of Multiple Variables in Large-Scale Datasets
|
Description :
The robustness of many of the statistical techniques, such as factor
analysis, applied in the social sciences rests upon the assumption of
item-level normality. However, when dealing with real data, these
assumptions are often not met. The Box-Cox transformation (Box & Cox,
1964) < http://www.jstor.org/stable/2984418> provides an optimal
transformation for non-normal variables. Yet, for large datasets of
continuous variables, its application in current software programs is
cumbersome with analysts having to take several steps to normalise each
variable. We present an R package \'normalr\' that enables researchers to
make convenient optimal transformations of multiple variables in
datasets. This R package enables users to quickly and accurately: (1)
anchor all of their variables at 1.00, (2) select the desired precision
with which the optimal lambda is estimated, (3) apply each unique
exponent to its variable, (4) rescale resultant values to within their
original X1 and X(n) ranges, and (5) provide original and transformed
estimates of skewness, kurtosis, and other inferential assessments of
normality.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
