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Higher-Order Growth Curves and Mixture Modeling with Mplus: A Practical Guide
Contributor(s): Wickrama, Kandauda A. S. (Author), Lee, Tae Kyoung (Author), O'Neal, Catherine Walker (Author)
ISBN: 0367711265     ISBN-13: 9780367711269
Publisher: Routledge
OUR PRICE:   $66.45  
Product Type: Paperback - Other Formats
Published: November 2021
Qty:
Additional Information
BISAC Categories:
- Psychology | Statistics
- Education | Statistics
- Business & Economics | Statistics
Dewey: 519.5
LCCN: 2021025885
Physical Information: 0.72" H x 7" W x 10" (1.33 lbs) 346 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

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 using normal and non-normal (e.g., categorical) data. 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.

New to this edition:

- Two new chapters providing a stepwise introduction and practical guide to the application of second-order growth curves and mixture models with categorical outcomes using Mplus program. Complete with exercises, answer keys, and downloadable data files.

- Updated illustrative examples using Mplus 8.0 include conceptual figures, Mplus program syntax, and an interpretation of results to show readers how to carry out the analyses with actual data.

This text is ideal for use in graduate courses or workshops 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) across the social and behaviorial sciences.