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# CITATION file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "EFAfactors" in publications use:'
type: software
license: GPL-3.0-only
title: 'EFAfactors: Determining the Number of Factors in Exploratory Factor Analysis'
version: 1.2.1
doi: 10.32614/CRAN.package.EFAfactors
abstract: 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) <https://doi.org/10.1207/s15327906mbr0102_10>,
  Kaiser-Guttman Criterion (KGC) by Guttman (1954) <https://doi.org/10.1007/BF02289162>
  and Kaiser (1960) <https://doi.org/10.1177/001316446002000116>, and flexible Parallel
  Analysis (PA) by Horn (1965) <https://doi.org/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)
  <https://doi.org/10.1037/met0000074>, Comparison Data (CD) by Ruscio and Roche (2012)
  <https://doi.org/10.1037/a0025697>, and Hull method by Lorenzo-Seva et al. (2011)
  <https://doi.org/10.1080/00273171.2011.564527>, as well as some AI-based methods
  like Comparison Data Forest (CDF) by Goretzko and Ruscio (2024) <https://doi.org/10.3758/s13428-023-02122-4>
  and Factor Forest (FF) by Goretzko and Buhner (2020) <https://doi.org/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.
authors:
- family-names: Qin
  given-names: Haijiang
  email: haijiang133@outlook.com
  orcid: https://orcid.org/0009-0000-6721-5653
- family-names: Guo
  given-names: Lei
  email: happygl1229@swu.edu.cn
  orcid: https://orcid.org/0000-0002-8273-3587
repository: https://haijiangq.r-universe.dev
commit: 501c0d3dcb3e29cb8b3558fd0e83ac01a996026a
url: https://haijiangqin.com/EFAfactors/
date-released: '2025-02-15'
contact:
- family-names: Qin
  given-names: Haijiang
  email: haijiang133@outlook.com
  orcid: https://orcid.org/0009-0000-6721-5653