Fast and Flexible Implementations of Exploratory Factor Analysis Tools R package EFAtools version 1.0.0 Provides a complete workflow for exploratory factor analysis (EFA). It covers data screening and factorability checks, a suite of factor retention criteria for choosing the number of factors, and factor extraction by principal axis factoring, maximum likelihood, unweighted least squares, or diagonally weighted least squares from Pearson, Spearman, Kendall, polychoric, tetrachoric, or two-stage full-information maximum likelihood correlations. A built-in rotation engine offers a range of orthogonal and oblique rotations, and standard errors for loadings and related quantities can be obtained by analytic, robust, or bootstrap methods. Further tools support model averaging across analytic choices, multigroup EFA with factor congruence, EFA on multiply imputed data, Schmid-Leiman transformation, reliability coefficients (including McDonald's omegas), factor score estimation, data simulation, and power analysis. Computationally intensive procedures are implemented in 'C++' for speed. Software Depends: R (>= 4.1.0) Imports: psych, stats, ggplot2 (>= 3.4.0), cli, Rcpp, future.apply, checkmate, progressr, rlang, clue, lifecycle LinkingTo: Rcpp, RcppArmadillo, roptim Suggests: testthat (>= 3.0.0), future, GPArotation (>= 2022.4-1), lavaan, lavaan.mi, MASS, mice, knitr, rmarkdown, vdiffr, polycor, mnormt, fungible, semTools, withr Markus Steiner <markus.d.steiner@gmail.com> Comprehensive R Archive Network (CRAN) Markus Steiner [aut, cre] (ORCID: <https://orcid.org/0000-0002-8126-0757>), Silvia Steiner [aut] (ORCID: <https://orcid.org/0000-0002-0118-7722>), William Revelle [ctb], Max Auerswald [ctb], Morten Moshagen [ctb], John Ruscio [ctb], Brendan Roche [ctb], Urbano Lorenzo-Seva [ctb], David Navarro-Gonzalez [ctb], Johan Braeken [ctb], Andreas Soteriades [ctb] GPL-3 2026-07-23 application/tgz https://CRAN.R-project.org/package=EFAtools doi:10.32614/CRAN.package.EFAtools