FactorAssumptions: Set of Assumptions for Factor and Principal Component Analysis

Tests for Kaiser-Meyer-Olkin (KMO) and communalities in a dataset. It provides a final sample by removing variables in a iterable manner while keeping account of the variables that were removed in each step. It follows the best practices and assumptions according to Hair, Black, Babin & Anderson (2018, ISBN:9781473756540).

Version: 2.0.1
Depends: R (≥ 3.6.0), MASS, psych
Suggests: knitr, rmarkdown, testthat (≥ 2.1.0)
Published: 2022-03-08
DOI: 10.32614/CRAN.package.FactorAssumptions
Author: Jose Storopoli ORCID iD [aut, cre]
Maintainer: Jose Storopoli <jstoropoli at protonmail.com>
BugReports: https://github.com/storopoli/FactorAssumptions/issues
License: GPL-3
URL: https://github.com/storopoli/FactorAssumptions
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: FactorAssumptions results

Documentation:

Reference manual: FactorAssumptions.html , FactorAssumptions.pdf
Vignettes: How to use FactorAssumptions (source, R code)

Downloads:

Package source: FactorAssumptions_2.0.1.tar.gz
Windows binaries: r-devel: FactorAssumptions_2.0.1.zip, r-release: FactorAssumptions_2.0.1.zip, r-oldrel: FactorAssumptions_2.0.1.zip
macOS binaries: r-release (arm64): FactorAssumptions_2.0.1.tgz, r-oldrel (arm64): FactorAssumptions_2.0.1.tgz, r-release (x86_64): FactorAssumptions_2.0.1.tgz, r-oldrel (x86_64): FactorAssumptions_2.0.1.tgz
Old sources: FactorAssumptions archive

Linking:

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