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date: 08 April 2020

Abstract and Keywords

The focus of this chapter is on the principles and methods of latent variable measurement models in applied research. After a review of the common factor model, examples of exploratory factor analysis and confirmatory factor analysis are provided along with a recently developed hybrid of these two approaches (exploratory structural equation modeling). In addition, more advanced applications are illustrated, including multiple-group models, to evaluate measurement invariance and population heterogeneity, and various types of higher-order factor models (e.g., second-order factor analysis, bifactor models). Future directions are discussed, including more recent advances in these methodologies (e.g., factor mixture models, multilevel factor models, nonlinear factor models).

Keywords: common factor model, latent variable, exploratory factor analysis, confirmatory factor analysis, exploratory structural equation modeling, measurement invariance, multiple-group solutions, higher-order factor analysis, bifactor model

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