Package: EFAfactors
Type: Package
Title: Determining the Number of Factors in Exploratory Factor Analysis
Version: 1.1.0
Date: 2024-09-29
Authors@R: c(person(given = "Haijiang", family = "Qin", role = c("aut", "cre", "cph"), email = "haijiang133@outlook.com"),
             person(given = "Lei", family = "Guo", role = c("aut", "cph"), email = "happygl1229@swu.edu.cn"))
Maintainer: Haijiang Qin <haijiang133@outlook.com>
Description: Provides a collection of standard factor retention methods in Exploratory Factor Analysis (EFA), making it easier to determine the number of factors. Traditional methods such as the scree plot by Cattell (1966) <doi:10.1207/s15327906mbr0102_10>, Kaiser-Guttman Criterion (KGC) by Guttman (1954) <doi:10.1007/BF02289162> and Kaiser (1960) <doi:10.1177/001316446002000116>, and flexible Parallel Analysis (PA) by Horn (1965) <doi:10.1007/BF02289447> based on eigenvalues form PCA or EFA are readily available. This package also implements several newer methods, such as the Empirical Kaiser Criterion (EKC) by Braeken and van Assen (2017) <doi:10.1037/met0000074>, Comparison Data (CD) by Ruscio and Roche (2012) <doi:10.1037/a0025697>, and Hull method by Lorenzo-Seva et al. (2011) <doi:10.1080/00273171.2011.564527>, as well as some AI-based methods like Comparison Data Forest (CDF) by Goretzko and Ruscio (2024) <doi:10.3758/s13428-023-02122-4> and Factor Forest (FF) by Goretzko and Buhner (2020) <doi:10.1037/met0000262>. Additionally, it includes a deep neural network (DNN) trained on large-scale datasets that can efficiently and reliably determine the number of factors.
License: GPL-3
Depends: R (>= 4.1.0)
Imports: BBmisc, ddpcr, ineq, MASS, Matrix, mlr, ParamHelpers, proxy,
        psych, ranger, reticulate, Rcpp, RcppArmadillo, SimCorMultRes,
        xgboost
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 7.3.2
Encoding: UTF-8
NeedsCompilation: yes
Collate: 'CD.R' 'CDF.R' 'data.bfi.R' 'data.datasets.R' 'data.scaler.R'
        'DNN_predictor.R' 'EFAhclust.R' 'EFAindex.R' 'EFAkmeans.R'
        'EFAvote.R' 'EKC.R' 'EFAscreet.R' 'EFAsim.data.R'
        'extractor.feature.DNN.R' 'extractor.feature.FF.R'
        'factor.analysis.R' 'FF.R' 'GenData.R' 'get.runs.R' 'Hull.R'
        'KGC.R' 'load.R' 'model.xgb.R' 'normalizor.R' 'PA.R' 'plot.R'
        'print.R' 'RcppExports.R' 'af.softmax.R' 'utils.R' 'zzz.R'
Repository: CRAN
Packaged: 2024-09-29 17:05:12 UTC; Haiji
Author: Haijiang Qin [aut, cre, cph],
  Lei Guo [aut, cph]
Date/Publication: 2024-09-29 22:40:14 UTC
Built: R 4.3.3; x86_64-apple-darwin20; 2024-09-29 23:06:17 UTC; unix
Archs: EFAfactors.so.dSYM
