Package: kfa 0.2.2
kfa: K-Fold Cross Validation for Factor Analysis
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.
Authors:
kfa_0.2.2.tar.gz
kfa_0.2.2.zip(r-4.5)kfa_0.2.2.zip(r-4.4)kfa_0.2.2.zip(r-4.3)
kfa_0.2.2.tgz(r-4.4-any)kfa_0.2.2.tgz(r-4.3-any)
kfa_0.2.2.tar.gz(r-4.5-noble)kfa_0.2.2.tar.gz(r-4.4-noble)
kfa_0.2.2.tgz(r-4.4-emscripten)kfa_0.2.2.tgz(r-4.3-emscripten)
kfa.pdf |kfa.html✨
kfa/json (API)
NEWS
| # Install 'kfa' in R: |
| install.packages('kfa', repos = c('https://knickodem.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/knickodem/kfa/issues
- example.kfa - Kfa results from simulated data example
cross-validationfactor-analysispsychometricsscale-development
Last updated 9 months agofrom:a91d785fe2. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Aug 23 2024 |
| R-4.5-win | OK | Aug 23 2024 |
| R-4.5-linux | OK | Aug 23 2024 |
| R-4.4-win | OK | Aug 23 2024 |
| R-4.4-mac | OK | Aug 23 2024 |
| R-4.3-win | OK | Aug 23 2024 |
| R-4.3-mac | OK | Aug 23 2024 |
Exports:agg_corsagg_loadingsagg_model_fitagg_relsefa_cfa_syntaxfind_kget_std_loadingsindex_availablek_model_fitkfakfa_reportmodel_structurerun_efawrite_efa
Dependencies:askpassbase64encbslibcachemcaretclasscliclockcodetoolscolorspacecommonmarkcpp11crayoncrulcurldata.tablediagramdigestdoParalleldplyre1071evaluatefansifarverfastmapflextablefontawesomefontBitstreamVerafontLiberationfontquiverforeachfsfuturefuture.applygdtoolsgenericsgfontsggplot2globalsgluegowerGPArotationgtablehardhathighrhtmltoolshttpcodehttpuvipredisobanditeratorsjquerylibjsonliteKernSmoothknitrlabelinglaterlatticelavalavaanlifecyclelistenvlubridatemagrittrMASSMatrixmemoisemgcvmimemnormtModelMetricsmunsellmvtnormnlmennetnumDerivofficeropensslparallellypbivnormpillarpkgconfigplyrpROCprodlimprogressrpromisesproxypurrrquadprogR6raggrappdirsRColorBrewerRcpprecipesreshape2rlangrmarkdownrpartsassscalessemToolsshapeshinysimstandardsourcetoolsSQUAREMstringistringrsurvivalsyssystemfontstextshapingtibbletidyrtidyselecttimechangetimeDatetinytextriebeardtzdburltoolsutf8uuidvctrsviridisLitewithrxfunxml2xtableyamlzip
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Aggregated factor correlations | agg_cors |
| Aggregated factor loadings | agg_loadings |
| Summary table of model fit | agg_model_fit |
| Aggregated scale reliabilities | agg_rels |
| Write confirmatory factor analysis syntax | efa_cfa_syntax |
| kfa results from simulated data example | example.kfa |
| Find k for k-fold cross-validation | find_k |
| Standardized factor loadings matrix | get_std_loadings |
| Available Fit Indices | index_available |
| Extract model fit | k_model_fit |
| Conducts k-fold cross validation for factor analysis | kfa |
| Creates summary report from a k-fold factor analysis | kfa_report |
| Unique factor structures | model_structure |
| Conducts exploratory factor analysis | run_efa |
| Write exploratory factor analysis syntax | write_efa |
