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>.
|Author||Vahid Nassiri [aut], Anikó Lovik [aut], Geert Molenberghs [aut], Geert Verbeke [aut], Tobias Busch [aut, cre] (<https://orcid.org/0000-0002-8390-7892>)|
|Maintainer||Tobias Busch <email@example.com>|
|License||MIT + file LICENSE|
|Package repository||View on CRAN|
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