Python Packages for Exploratory Factor Analysis. Issue 6 (2nd November 2021)

• Record Type: Journal Article
• Authors: Persson, Isaiah; Khojasteh, Jam
• Is Part Of: Structural equation modeling. Volume 28:Issue 6(2021)
• Page Start: 983
• Page End: 988
• Publication Date: 2021-11-02
• Subjects: Exploratory factor analysis (EFA) -- Python -- statsmodels -- FactorAnalyzer -- scikit-learn; Multivariate analysis -- Periodicals; Social sciences -- Statistical methods -- Periodicals; 519.535
• DOI: 10.1080/10705511.2021.1910037
• Languages: English
• ISSNs: 1070-5511

Abstract

ABSTRACT: Exploratory Factor Analysis (EFA) is a widely used statistical technique for reducing data dimensionality and representing latent constructs via observed variables. Different software offer toolsets for performing this analysis. While Python's statistical computing ecosystem is less developed than that of R, it is growing in popularity as a platform for data analysis and now offers several packages that perform EFA. This article reviews EFA modules in the statsmodels, FactorAnalyzer, and scikit-learn Python packages. These packages are discussed with regard to official documentation, features, and performance on an applied example.