Presents a useful guide for applications of SEM whilst systematically demonstrating various SEM models using Mplus Focusing on the conceptual and practical aspects of Structural Equation Modeling SEM this book demonstrates basic concepts and examples of various SEM models along with updates on many advanced methods including confirmatory factor analysis CFA with categorical items bifactor model Bayesian CFA model item response theory IRT model graded response model GRM multiple imputation MI of missing values plausible values of latent variables moderated mediation model Bayesian SEM latent growth modeling LGM with individually varying times of observations dynamic structural equation modeling DSEM residual dynamic structural equation modeling RDSEM testing measurement invariance of instrument with categorical variables longitudinal latent class analysis LLCA latent transition analysis LTA growth mixture modeling GMM with covariates and distal outcome manual implementation of the BCH method and the three step method for mixture modeling Monte Carlo simulation power analysis for various SEM models and estimate sample size for latent class analysis LCA model The statistical modeling program Mplus Version 8 2 is featured with all models updated It provides researchers with a flexible tool that allows them to analyze data with an easy to use interface and graphical displays of data and analysis results Intended as both a teaching resource and a reference guide and written in non mathematical terms Structural Equation Modeling: Applications Using Mplus 2nd edition provides step by step instructions of model specification estimation evaluation and modification Chapters cover: Confirmatory Factor Analysis CFA ; Structural Equation Models SEM ; SEM for Longitudinal Data; Multi Group Models; Mixture Models; and Power Analysis and Sample Size Estimate for SEM Presents a useful reference guide for applications of SEM while systematically demonstrating various advanced SEM models Discusses and demonstrates various SEM models using both cross sectional and longitudinal data with both continuous and categorical outcomes Provides step by step instructions of model specification and estimation as well as detailed interpretation of Mplus results using real data sets Introduces different methods for sample size estimate and statistical power analysis for SEM Structural Equation Modeling is an excellent book for researchers and graduate students of SEM who want to understand the theory and learn how to build their own SEM models using Mplus
