1. Introduction to Multilevel Modeling with IBM SPSS. 2. Preparing
and Examining the Data for Multilevel Analyses.
3. Defining a Basic Two-Level Multilevel Regression Model. 4. Three-Level Univariate Regression Models. 5. Examining Individual Change with Repeated Measures Data. 6. Applications of Mixed Models for Longitudinal Data.
7. Multivariate Multilevel Models. 8. Cross-Classified Multilevel Models. 9. Concluding Thoughts. Appendix A: Syntax Statements. Appendix B: Model Comparisons Across Software Applications. Appendix C: Syntax Routine to Estimate Rho from Model's Variance Components.
"Ronald Heck and his colleagues have provided academics, graduate students, and practitioners with a resource that few can surpass. This book contains excellent details for users with varying degrees of proficiency in multilevel modelling. It should be on the book shelf of anyone who claims to use this technique." - Timothy Teo, University of Auckland, New Zealand "This book serves, not only as an introduction to using IBM SPSS for multilevel models, but as a wonderful introduction to multilevel models through empirical example. It is a wonderful resource for an undergraduate or graduate course on multilevel modeling." - Kevin Grimm, University of California, Davis, USA"This book is ideal for individuals interested in learning about how to analyze different types of multilevel and longitudinal models using the MIXED procedure in IBM SPPS. The book methodically progresses from the simplest of models and designs to the more advanced ones. The presentation of statistical concepts is easy to follow, the data analysis examples are excellent, and the screen shots of the scripts and outputted results are thoroughly and effectively annotated." - George A. Marcoulides, University of California, Riverside, USA