Impute the covariance matrix of incomplete data so that factor analysis can be performed. Imputations are made using multiple imputation by Multivariate Imputation with Chained Equations (MICE) and combined with Rubin's rules. Parametric Fieller confidence intervals and nonparametric bootstrap confidence intervals can be obtained for the variance explained by different numbers of principal components. The method is described in Nassiri et al. (2018) <doi:10.3758/s13428-017-1013-4>.
Version: 0.2.1 Imports: stats, mice, dplyr, checkmate Suggests: psych, testthat, knitr, rmarkdown, ggplot2, tidyr, covr Published: 2025-05-10 DOI: 10.32614/CRAN.package.mifa Author: Vahid Nassiri [aut], Anikó Lovik [aut], Geert Molenberghs [aut], Geert Verbeke [aut], Tobias Busch [aut, cre] Maintainer: Tobias Busch <teebusch at gmail.com> BugReports: https://github.com/teebusch/mifa/issues License: MIT + file LICENSE URL: https://github.com/teebusch/mifa NeedsCompilation: no Materials: README NEWS CRAN checks: mifa results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=mifa to link to this page.
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4