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RGenData  

Generates Multivariate Nonnormal Data and Determines How Many Factors to Retain
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("RGenData", "1.0")



Attach the package and use:
library("RGenData")
Maintained by
John Ruscio
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-11-14
Latest Update: 2018-11-14
Description:
The GenDataSample() and GenDataPopulation() functions create, respectively, a sample or population of multivariate nonnormal data using methods described in Ruscio and Kaczetow (2008). Both of these functions call a FactorAnalysis() function to reproduce a correlation matrix. The EFACompData() function allows users to determine how many factors to retain in an exploratory factor analysis of an empirical data set using a method described in Ruscio and Roche (2012). The latter function uses populations of comparison data created by calling the GenDataPopulation() function. <doi:10.1080/00273170802285693>. <doi:10.1037/a0025697>.
How to cite:
John Ruscio (2018). RGenData: Generates Multivariate Nonnormal Data and Determines How Many Factors to Retain. R package version 1.0, https://cran.r-project.org/web/packages/RGenData
Previous versions and publish date:
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Functions, R codes and Examples using the RGenData R package
Some associated functions: EFACompData . FactorAnalysis . GenDataPopulation . GenDataSample . 
Some associated R codes: EFAGenData.R .  Full RGenData package functions and examples
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