General Structural Equation Modeling

Abstract

The most general structural equation models treated in this book are nothing more—and nothing less—than path analytical models (introduced in Chapter 1) that involve latent variables (discussed in Chapter 2). Even though classical path analysis has important advantages over conventional univariate or multivariate regression (e.g., the estimation of direct and indirect structural effects), one major disadvantage is that a priori hypothesized structures can be analyzed only under the usually unrealistic assumption that variables in the models are measured with no or negligible error. An integration of latent variables—as previously introduced in the context of confirmatory factor analysis—into path models relaxes this assumption and allows for the estimation of direct and indirect structural effects between variables or constructs that are not directly observable but, instead, are indicated by some imperfect observable measures.KeywordsStructural EquationStructural Equation ModelingGeneralize Little SquareConfirmatory Factor Analysis ModelLagrange Multiplier TestThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.