Multiple Imputation for Exploratory Factor Analysis

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) .


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("mifa")

0.2.0 by Tobias Busch, 8 months ago


https://github.com/teebusch/mifa


Report a bug at https://github.com/teebusch/mifa/issues


Browse source code at https://github.com/cran/mifa


Authors: Vahid Nassiri [aut] , Anikó Lovik [aut] , Geert Molenberghs [aut] , Geert Verbeke [aut] , Tobias Busch [aut, cre]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports stats, mice, dplyr, checkmate

Suggests psych, testthat, knitr, rmarkdown, ggplot2, tidyr, covr


See at CRAN