Fast and Flexible Implementations of Exploratory Factor Analysis Tools

Provides functions to perform exploratory factor analysis (EFA) procedures and compare their solutions. The goal is to provide state-of-the-art factor retention methods and a high degree of flexibility in the EFA procedures. This way, for example, implementations from R 'psych' and 'SPSS' can be compared. Moreover, functions for Schmid-Leiman transformation and the computation of omegas are provided. To speed up the analyses, some of the iterative procedures, like principal axis factoring (PAF), are implemented in C++.


Reference manual

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0.3.0 by Markus Steiner, 4 months ago

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Authors: Markus Steiner [aut, cre] , Silvia Grieder [aut] , William Revelle [ctb] , Max Auerswald [ctb] , Morten Moshagen [ctb] , John Ruscio [ctb] , Brendan Roche [ctb] , Urbano Lorenzo-Seva [ctb] , David Navarro-Gonzalez [ctb]

Documentation:   PDF Manual  

GPL-3 license

Imports lavaan, psych, crayon, stringr, stats, ggplot2, tibble, magrittr, dplyr, cli, Rcpp, viridisLite, graphics, future.apply, future, GPArotation, checkmate, tidyr, progressr, progress, rlang

Suggests testthat, knitr, rmarkdown, microbenchmark

Linking to Rcpp, RcppArmadillo

Imported by EFA.dimensions.

See at CRAN