[aut, cre]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: | 1.1.2 |
| Depends: | R (≥ 3.6.0), MASS, psych |
| Suggests: | knitr, rmarkdown, testthat (≥ 2.1.0) |
| Published: | 2020-03-06 |
| Author: | Jose Storopoli
[aut, cre] |
| Maintainer: | Jose Storopoli <thestoropoli at gmail.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 |
| Reference manual: | FactorAssumptions.pdf |
| Vignettes: |
How to use FactorAssumptions |
| Package source: | FactorAssumptions_1.1.2.tar.gz |
| Windows binaries: | r-devel: FactorAssumptions_1.1.2.zip, r-release: FactorAssumptions_1.1.2.zip, r-oldrel: FactorAssumptions_1.1.2.zip |
| macOS binaries: | r-release: FactorAssumptions_1.1.2.tgz, r-oldrel: FactorAssumptions_1.1.2.tgz |
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