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Exploratory factor analysis

About: Exploratory factor analysis is a research topic. Over the lifetime, 9311 publications have been published within this topic receiving 248406 citations.


Papers
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Journal Article
TL;DR: In this paper, the authors collect, in one article, information that will allow researchers and practitioners to understand the various choices available through popular software packages, and to make decisions about "best practices" in exploratory factor analysis.
Abstract: Exploratory factor analysis (EFA) is a complex, multi-step process. The goal of this paper is to collect, in one article, information that will allow researchers and practitioners to understand the various choices available through popular software packages, and to make decisions about ”best practices” in exploratory factor analysis. In particular, this paper provides practical information on making decisions regarding (a) extraction, (b) rotation, (c) the number of factors to interpret, and (d) sample size.

7,865 citations

Book
01 Jan 2006
TL;DR: In this article, the authors present a detailed, worked-through example drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology.
Abstract: "With its emphasis on practical and conceptual aspects, rather than mathematics or formulas, this accessible book has established itself as the go-to resource on confirmatory factor analysis (CFA). Detailed, worked-through examples drawn from psychology, management, and sociology studies illustrate the procedures, pitfalls, and extensions of CFA methodology. The text shows how to formulate, program, and interpret CFA models using popular latent variable software packages (LISREL, Mplus, EQS, SAS/CALIS); understand the similarities and differences between CFA and exploratory factor analysis (EFA); and report results from a CFA study. It is filled with useful advice and tables that outline the procedures. The companion website offers data and program syntax files for most of the research examples, as well as links to CFA-related resources. New to This Edition *Updated throughout to incorporate important developments in latent variable modeling. *Chapter on Bayesian CFA and multilevel measurement models. *Addresses new topics (with examples): exploratory structural equation modeling, bifactor analysis, measurement invariance evaluation with categorical indicators, and a new method for scaling latent variables. *Utilizes the latest versions of major latent variable software packages"--

7,620 citations

Journal ArticleDOI
TL;DR: This paper reviewed the major design and analytical decisions that must be made when conducting exploratory factor analysis and notes that each of these decisions has important consequences for the obtained results, and the implications of these practices for psychological research are discussed.
Abstract: Despite the widespread use of exploratory factor analysis in psychological research, researchers often make questionable decisions when conducting these analyses. This article reviews the major design and analytical decisions that must be made when conducting a factor analysis and notes that each of these decisions has important consequences for the obtained results. Recommendations that have been made in the methodological literature are discussed. Analyses of 3 existing empirical data sets are used to illustrate how questionable decisions in conducting factor analyses can yield problematic results. The article presents a survey of 2 prominent journals that suggests that researchers routinely conduct analyses using such questionable methods. The implications of these practices for psychological research are discussed, and the reasons for current practices are reviewed.

7,590 citations

Journal ArticleDOI
TL;DR: Practical information on making decisions regarding (a) extraction, (b) rotation, (c) the number of factors to interpret, and (d) sample size is provided.

6,726 citations

Journal ArticleDOI
TL;DR: A survey of approaches to measurement in socobehavioral research can be found in this paper, where the authors present a survey of the most common approaches to measuring in sociology research.
Abstract: Contents: Preface. Overview. Part I: Measurement. Measurement and Scientific Inquiry. Criterion-Related Validation. Construct Validation. Reliability. Selected Approaches to Measurement in Sociobehavioral Research. Part II: Design. Science and Scientific Inquiry. Definitions and Variables. Theories, Problems, and Hypotheses. Research Design: Basic Principles and Concepts. Artifacts and Pitfalls in Research. Experimental Designs. Quasi-Experimental Designs. Nonexperimental Designs. Introduction to Sampling. Part III: Analysis. Computers and Computer Programs. Simple Regression Analysis. Multiple Regression Analysis. A Categorical Independent Variable. Multiple Categorical Independent Variables: Factorial Designs. Attribute--Treatments--Interactions Analysis of Covariance. Exploratory Factor Analysis. Confirmatory Factor Analysis. Structural Equation Modeling. Appendices: Critical Values for F. Percentile Points for X2 Distribution.

3,942 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20231,251
20222,776
20211,013
2020936
2019763
2018710