Package: FAfA
Title: Factor Analysis for All
Version: 1.4.1
Date: 2026-10-01
Authors@R: c(
    person("Abdullah Faruk", "KILIC", , "afarukkilic@trakya.edu.tr", role = c("aut", "cre", "cph")),
    person("Ahmet", "Caliskan", , "ahmetcaliskan1987@gmail.com", role = c("aut", "cph")),
    person("Melissa G.", "Wolf", , "missgord@gmail.com", role = c("ctb", "cph"),
           comment = "Dynamic Fit Index methodology and upstream implementation"),
    person("Daniel", "McNeish", , "dmcneish@asu.edu", role = c("ctb", "cph"),
           comment = "Dynamic Fit Index methodology and upstream implementation"),
    person("Brian P.", "O'Connor", role = c("ctb", "cph"),
           comment = "MAP and Empirical Kaiser Criterion upstream implementation")
  )
Description: Provides a comprehensive Shiny-based graphical user interface
    for conducting a wide range of factor analysis procedures. 'FAfA'
    (Factor Analysis for All) guides users through data uploading,
    assumption checking (descriptive statistics, collinearity, multivariate
    normality, outliers), data wrangling (variable exclusion, data
    splitting), exploratory factor analysis (EFA) with various rotation
    and extraction methods, confirmatory factor analysis (CFA), reliability
    analysis (e.g., Cronbach's Alpha, McDonald's Omega), and measurement
    invariance testing across groups. Factor retention methods include
    parallel analysis following Horn (1965) <doi:10.1007/BF02289447>,
    optimized parallel analysis following Timmerman and Lorenzo-Seva
    (2011) <doi:10.1037/a0023353>, permutation parallel analysis for
    categorical variables following Lubbe (2019) <doi:10.1037/met0000171>,
    the Hull method following Lorenzo-Seva et al. (2011)
    <doi:10.1080/00273171.2011.564527>, minimum average partial criteria
    following Velicer (1976) <doi:10.1007/BF02293557> and O'Connor (2000)
    <doi:10.3758/BF03200807>, and the empirical Kaiser criterion following
    Braeken and van Assen (2017) <doi:10.1037/met0000074>. Exploratory graph
    analysis follows Golino and Epskamp (2017)
    <doi:10.1371/journal.pone.0174035>, with bootstrap stability assessment
    following Christensen and Golino (2021) <doi:10.3390/psych3030032>.
    Internal split-sample EFA replication follows Osborne and Fitzpatrick
    (2012) <doi:10.7275/h0bd-4d11>. Model-specific dynamic fit index cutoffs
    for CFA follow McNeish and Wolf (2023) <doi:10.1037/met0000425>.
    Item weighting follows Kılıç (2026) <doi:10.3758/s13428-026-03095-w>.
    Analyses use established R packages such as 'lavaan' and 'psych'.
    Results are presented in tables and plots with downloadable outputs.
    Analysis projects can be saved and restored, and reproducible R, HTML,
    and PDF workflow reports can be generated.
License: AGPL-3
Copyright: See file inst/COPYRIGHTS.
Depends: R (>= 4.1.0)
URL: https://github.com/AFarukKILIC/FAfA
BugReports: https://github.com/AFarukKILIC/FAfA/issues
Imports: Amelia, EFA.MRFA, EGAnet (>= 2.4.1), ItemRest, bsicons, bslib,
        ggplot2, golem, grDevices, graphics, haven, lavaan, mice,
        missForest, mvnormalTest, naniar, psych, qgraph, readxl,
        semPlot, shiny, shinycssloaders, stats, tools, utils
Suggests: flextable, officer, shinytest2, spelling, testthat (>= 3.0.0)
Config/testthat/edition: 3
Encoding: UTF-8
Language: en-US
Config/roxygen2/version: 8.1.0
NeedsCompilation: no
Packaged: 2026-10-01 12:42:24 UTC; Faruk
Author: Abdullah Faruk KILIC [aut, cre, cph],
  Ahmet Caliskan [aut, cph],
  Melissa G. Wolf [ctb, cph] (Dynamic Fit Index methodology and upstream
    implementation),
  Daniel McNeish [ctb, cph] (Dynamic Fit Index methodology and upstream
    implementation),
  Brian P. O'Connor [ctb, cph] (MAP and Empirical Kaiser Criterion
    upstream implementation)
Maintainer: Abdullah Faruk KILIC <afarukkilic@trakya.edu.tr>
Repository: CRAN
Date/Publication: 2026-10-01 15:41:09 UTC
