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) .


Reference manual

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


0.2.0 by Tobias Busch, a month ago

Report a bug at

Browse source code at

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