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Latent Variable Modeling Using R
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Table of Contents

Preface. 1. Introduction to R. 2. Path Models and Analysis. 3. Basic Latent Variable Models. 4. Latent Variable Models with Multiple Groups. 5. Models with Multiple Time Periods. 6. Models with Dichotomous Indicator Variables. 7. Models with Missing Data. 8. Sample Size Planning. 9. Hierarchical Latent Variable Models. Appendix A. Measures of Model Fit. Appendix B. Additional Packages. Appendix C. Exercise Answers. Glossary.

About the Author

A. Alexander Beaujean is an Associate Professor in Educational Psychology at Baylor University.

Reviews

"This is a very well written book on an important contemporary topic. Readers will delight in its eloquent prose and mathematics. This book should be taken seriously." - John J. McArdle, University of Southern California, USA "This book is a wonderful resource for instructors who are contemplating migrating their SEM courses to R. The book begins with a nice introduction to R. Subsequent chapters nicely introduce latent variable topics and demonstrate effectively how the lavaan package can be utilized to fit models. Each chapter ends with examples that can be utilized as in-class examples or given as homework problems." - Jeffrey R. Harring, University of Maryland, USA "A book for every scholar's shelf: pertinent, thorough, practical, accurate, and especially, readable." - Steven J. Osterlind, University of Missouri, USA "This book ... provide[s] students and researchers with a structural equation modeling book which deals with R ... the Lavaan module. ... The book walks the reader through some of the R code necessary to do the analyses. ... [This] book will be a "how to" resource for students and researchers to do their analyses in R. ... [It] ... has an easy ... humorous narrative style, which would also serve to reduce anxiety for the introductory reader." - Phil Wood, University of Missouri - Columbia, USA "The concepts are delivered in a clear, easy-to-follow manner. ...The hands-on examples ... take a person who does not know much about structural equation modeling and/or R to fit different latent variable models. ... [This book] will attract a lot of attention from students and/or professionals who want to use latent variable modeling in their studies and research. ... I will recommend [it] to my colleague who teach ... latent variable modelling ... [and] ... multivariate statistics." - Yanyan Sheng, Southern Illinois University at Carbondale, USA "A text is sorely needed that helps students understand latent variable models and at the same time help them apply what they learn with R. ... This text would be useful for three of [our] courses ... Educational Research, Item Response Theory, and Structural Equation Modeling. ... I found the material to be written at the level needed by our students." - Darrell M. Hull, University of North Texas, USA

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