Exploratory and Confirmatory Factor Analysis in Gifted Education: Examples with Self-Concept Data

Abstract

Factor analysis allows researchers to conduct exploratory analyses of latent variables, reduce data in large datasets, and test specific models. The purpose of this paper is to review common uses of factor analysis, provide general guidelines for best practices, illustrate these guidelines with examples using previously published self-concept data, and discuss common pitfalls and ways to avoid them.