{"title":"How many factors to retain in exploratory factor analysis? A critical overview of factor retention methods.","authors":"David Goretzko","doi":"10.1037/met0000733","DOIUrl":null,"url":null,"abstract":"<p><p>Determining the number of factors is a decisive, yet very difficult decision a researcher faces when conducting an exploratory factor analysis (EFA). Over the last decades, numerous so-called factor retention criteria have been developed to infer the latent dimensionality from empirical data. While some tutorials and review articles on EFA exist which give recommendations on how to determine the number of latent factors, there is no comprehensive overview that categorizes the existing approaches and integrates the results of existing simulation studies evaluating the various methods in different data conditions. With this article, we want to provide such an overview enabling (applied) researchers to make an informed decision when choosing a factor retention criterion. Summarizing the most important results from recent simulation studies, we provide guidance when to rely on which method and call for a more thoughtful handling of overly simple heuristics. (PsycInfo Database Record (c) 2025 APA, all rights reserved).</p>","PeriodicalId":20782,"journal":{"name":"Psychological methods","volume":" ","pages":""},"PeriodicalIF":7.6000,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Psychological methods","FirstCategoryId":"102","ListUrlMain":"https://doi.org/10.1037/met0000733","RegionNum":1,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PSYCHOLOGY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Determining the number of factors is a decisive, yet very difficult decision a researcher faces when conducting an exploratory factor analysis (EFA). Over the last decades, numerous so-called factor retention criteria have been developed to infer the latent dimensionality from empirical data. While some tutorials and review articles on EFA exist which give recommendations on how to determine the number of latent factors, there is no comprehensive overview that categorizes the existing approaches and integrates the results of existing simulation studies evaluating the various methods in different data conditions. With this article, we want to provide such an overview enabling (applied) researchers to make an informed decision when choosing a factor retention criterion. Summarizing the most important results from recent simulation studies, we provide guidance when to rely on which method and call for a more thoughtful handling of overly simple heuristics. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
期刊介绍:
Psychological Methods is devoted to the development and dissemination of methods for collecting, analyzing, understanding, and interpreting psychological data. Its purpose is the dissemination of innovations in research design, measurement, methodology, and quantitative and qualitative analysis to the psychological community; its further purpose is to promote effective communication about related substantive and methodological issues. The audience is expected to be diverse and to include those who develop new procedures, those who are responsible for undergraduate and graduate training in design, measurement, and statistics, as well as those who employ those procedures in research.