doi:10.1037/cbs0000069> with a cross validation technique that maximizes the available data (Hastie, Tibshirani, & Friedman, 2009) . Also available are functions to determine k by drawing on power analytic techniques for covariance structures (MacCallum, Browne, & Sugawara, 1996) <doi:10.1037/1082-989X.1.2.130>, generate model syntax, and summarize results in a report.">

kfa: K-Fold Cross Validation for Factor Analysis (original) (raw)

Provides functions to identify plausible and replicable factor structures for a set of variables via k-fold cross validation. The process combines the exploratory and confirmatory factor analytic approach to scale development (Flora & Flake, 2017) <doi:10.1037/cbs0000069> with a cross validation technique that maximizes the available data (Hastie, Tibshirani, & Friedman, 2009) isbn:978-0-387-21606-5. Also available are functions to determine k by drawing on power analytic techniques for covariance structures (MacCallum, Browne, & Sugawara, 1996) <doi:10.1037/1082-989X.1.2.130>, generate model syntax, and summarize results in a report.

Version: 0.2.2
Depends: R (≥ 3.6)
Imports: caret, doParallel, flextable (≥ 0.6.3), foreach, GPArotation, knitr, lavaan (≥ 0.6.9), officer, parallel, rmarkdown, semTools (≥ 0.5.5), simstandard
Suggests: semPlot
Published: 2023-07-09
DOI: 10.32614/CRAN.package.kfa
Author: Kyle Nickodem [aut, cre] and Peter Halpin [aut]
Maintainer: Kyle Nickodem <kyle.nickodem at gmail.com>
BugReports: https://github.com/knickodem/kfa/issues
License: GPL (≥ 3)
URL: https://github.com/knickodem/kfa
NeedsCompilation: no
Citation: kfa citation info
Materials: README, NEWS
CRAN checks: kfa results

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