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normalr  

Normalisation of Multiple Variables in Large-Scale Datasets
View on CRAN: Click here


Download and install normalr package within the R console
Install from CRAN:
install.packages("normalr")

Install from Github:
library("remotes")
install_github("cran/normalr")

Install by package version:
library("remotes")
install_version("normalr", "1.0.0")



Attach the package and use:
library("normalr")
Maintained by
Kevin Chang
[Scholar Profile | Author Map]
First Published: 2016-12-20
Latest Update: 2018-03-30
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) 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.
How to cite:
Kevin Chang (2016). normalr: Normalisation of Multiple Variables in Large-Scale Datasets. R package version 1.0.0, https://cran.r-project.org/web/packages/normalr. Accessed 06 Apr. 2025.
Previous versions and publish date:
0.0.1 (2016-12-20 13:02), 0.0.2 (2017-01-09 15:17), 0.0.3 (2017-01-17 08:36)
Other packages that cited normalr R package
View normalr citation profile
Other R packages that normalr depends, imports, suggests or enhances
Complete documentation for normalr
Functions, R codes and Examples using the normalr R package
Some associated functions: getLambda . normalise . normaliseData . normalrShiny . testData . 
Some associated R codes: getLambda.R . normalise.R . normaliseData.R . normalrShiny.R . testData.R .  Full normalr package functions and examples
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