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FAfA  

Factor Analysis for All
View on CRAN: Click here


Download and install FAfA package within the R console
Install from CRAN:
install.packages("FAfA")

Install from Github:
library("remotes")
install_github("cran/FAfA")

Install by package version:
library("remotes")
install_version("FAfA", "0.2")



Attach the package and use:
library("FAfA")
Maintained by
Abdullah Faruk KILIC
[Scholar Profile | Author Map]
First Published: 2024-07-09
Latest Update: 2024-07-09
Description:
This Shiny application offers researchers a comprehensive tool for performing factor analysis. Users can upload datasets, validate assumptions, manage missing and outlier data, split data for different analyses, and run exploratory and confirmatory factor analyses ("EFA" and "CFA"). The software also offers reliability analysis, exploratory graph analysis, and item weighting. With a user-friendly interface, this tool simplifies the EFA and CFA processes. The main features are data submission and simple data inspection. Data manipulation (excluding variables, splitting data, checking for outliers), assumption checking (Tabachnik & Fidell (2012) <ISBN:978-0-205-84957-4> and Field (2009) <ISBN:978-1-84787-906-6>) for factor analysis, exploratory factor analysis (with various factor number determination methods (Lorenzo-Seva & Ferrando (2021) <doi:10.5964/meth.7185>)), confirmatory factor analysis (model definition and modification suggestions (Kline (2011) <ISBN:978-1-60623-877-6>)), reliability analysis (Cronbach's alpha, McDonald's omega, Armor's theta, structural reliability, stratified alpha), item weighting (Kilic & Dogan (2019) <doi:10.21031/epod.516057>).
How to cite:
Abdullah Faruk KILIC (2024). FAfA: Factor Analysis for All. R package version 0.2, https://cran.r-project.org/web/packages/FAfA. Accessed 04 May. 2025.
Previous versions and publish date:
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Complete documentation for FAfA
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Full FAfA package functions and examples
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