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Higher-Order Growth Curves and Mixture Modeling with Mplus : A Practical Guide

Posted By: readerXXI
Higher-Order Growth Curves and Mixture Modeling with Mplus : A Practical Guide

Higher-Order Growth Curves and Mixture Modeling with Mplus :
A Practical Guide

by Kandauda K.A.S. Wickrama and Tae Kyoung Lee
English | 2016 | ISBN: 1138925152 | 347 Pages | PDF | 19 MB

This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book's datasets are available on the web.

Highlights include:

- Illustrative examples using Mplus 7.4 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data.
- Exercises with an answer key allow readers to practice the skills they learn.
- Applications to a variety of disciplines appeal to those in the behavioral, social, political, educational, occupational, business, and health sciences.
- Point to Remember boxes aid in reader comprehension or provide in-depth discussions of key statistical or theoretical concepts.

Ideal as a supplement for use in graduate courses on (advanced) structural equation, multilevel, longitudinal, or latent variable modeling, latent growth curve and mixture modeling, factor analysis, multivariate statistics, or advanced quantitative techniques (methods) taught in psychology, human development and family studies, business, education, health, and social sciences, this book's practical approach also appeals to researchers. Prerequisites include a basic knowledge of intermediate statistics and structural equation modeling.