kfa: K-Fold Cross Validation for Factor Analysis
Provides functions to explore possible factor structures for a set of variables and
helps identify plausible and replicable structures 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. 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: |
0.2.0 |
| Depends: |
R (≥ 3.6) |
| Imports: |
caret, doParallel, flextable (≥ 0.6.3), foreach, GPArotation, knitr, lavaan (≥ 0.6.9), officer, parallel, rmarkdown, semPlot, semTools (≥ 0.5.5), simstandard |
| Published: |
2022-02-21 |
| 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 |
Documentation:
Downloads:
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