Ideal for researchers and graduate students in the social sciences who require knowledge of structural equation modeling techniques to answer substantive research questions, Using Mplus for Structural Equation Modeling provides a reader-friendly introduction to the major types of structural equation models implemented in the Mplus framework. This practical book, which updates author E. Kevin Kelloway’s 1998 book Using LISREL for Structural Equation Modeling, retains the successful five-step process employed in the earlier book, with a thorough update for use in the Mplus environment. Kelloway provides an overview of structural equation modeling techniques in Mplus, including the estimation of confirmatory factor analysis and observed variable path analysis. He also covers multilevel modeling for hypothesis testing in real life settings and offers an introduction to the extended capabilities of Mplus, such as exploratory structural equation modeling and estimation and testing of mediated relationships. A sample application with the source code, printout, and results is presented for each type of analysis.

Latent Variable Path Analysis

The true power of structural equation modeling is the ability to estimate a complete model incorporating both measurement and structural considerations. In this chapter, we consider such a latent variable path analysis. Thus, in conducting the analysis, we will be equally concerned with assessing the proposed measurement relations (i.e., through confirmatory factor analysis) and the proposed structural relations (i.e., through path analysis). Although latent variable models can be complex, in actuality we are merely combining techniques we have covered in previous chapters. Moreover, although I will not be repeating this material, testing equality constraints, mediation, and multisample models can all be implemented with latent variables, just as they were with observed variable path analyses in the preceding chapter.

Model Specification

To illustrate ...

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