Current Methodological Considerations in Exploratory and Confirmatory Factor Analysis

TLDR

Researchers must make numerous choices when conducting factor analyses, each of which can significantly affect model results. This article offers an up‑to‑date overview of methodological choices in exploratory and confirmatory factor analysis and discusses how to select between them. It reviews key decisions—including sample size, model specification, estimation, factor determination, fit evaluation, and rotation—and illustrates current best practices. Despite persistent use of outdated methods, the article demonstrates contemporary approaches to improve factor analysis.

Abstract

Researchers must make numerous choices when conducting factor analyses, each of which can have significant ramifications on the model results. They must decide on an appropriate sample size to achieve accurate parameter estimates and adequate power, a factor model and estimation method, a method for determining the number of factors and evaluating model fit, and a rotation criterion. Unfortunately, researchers continue to use outdated methods in each of these areas. The present article provides a current overview of these areas in an effort to provide researchers with up-to-date methods and considerations in both exploratory and confirmatory factor analysis. A demonstration was provided to illustrate current approaches. Choosing between confirmatory and exploratory methods is also discussed, as researchers often make incorrect assumptions about the application of each.