Multilevel Modeling of Categorical Outcomes Using IBM SPSS

This is the first workbook that introduces readers to the multilevel approach to modeling with categorical outcomes using IBM SPSS Version 20. Readers learn how to set up, estimate, and interpret multilevel models with categorical outcomes. The authors walk readers step-by-step through data management, model conceptualization, and model specification issues related to single-level and multilevel models with categorical outcomes. Numerous annotated screen shots clearly demonstrate the use of the techniques and how to navigate through the program. Modeling syntax is also provided in the book’s appendix for users who prefer this approach to model development. Diagnostic tools and data management issues are introduced throughout. Examples of various types of categorical outcomes demonstrate how to set up each model and interpret the output. Extended examples in each chapter illustrate the logic of model development, interpretation of output, the context of the research questions, and the steps around which the analyses are structured. Readers can work with the examples developed in each chapter by using the corresponding data and syntax files available at www.psypress.com/9781848729568 .
The book opens with a review of conceptual and methodological issues associated with investigating multilevel and longitudinal models with categorical outcomes, followed by a chapter on IBM SPSS data management techniques to facilitate working with multilevel and longitudinal data sets. Chapters 3 and 4 detail the basics of the single-level and multilevel generalized linear model for various types of categorical outcomes, trouble-shooting techniques for common programming, and typical modeling problems and solutions readers are likely to encounter. Next population-average and unit-specific longitudinal models for investigating individual or organizational developmental processes are developed. Chapter 6 focuses on single- and multilevel models using multinomial and ordinal data followed by a chapter on models for count data. The book concludes with tips for expanding on the multilevel and longitudinal modeling techniques introduced.
Ideal as a supplement for graduate level courses and/or professional workshops on multilevel, longitudinal, latent variable modeling, multivariate statistics, and/or advanced quantitative techniques taught in psychology, business, education, health, and sociology, this practical workbook also appeals to researchers in these fields. An excellent follow up to the authors’ highly successful Multilevel and Longitudinal Modeling with IBM SPSS and Introduction to Multilevel Modeling Techniques, 2nd Edition this book can also be used with any multilevel and/or longitudinal book or as a stand-alone text introducing multilevel modeling with categorical outcomes.

Author Biography

Ronald Heck is professor of education at the University of Hawai’i at Manoa. His areas of interest include organizational theory, leadership, policy, and quantitative research methods. Scott L. Thomas is professor in the School of Educational Studies at Claremont Graduate University. His specialties include sociology of education, policy, and quantitative research methods. Lynn Tabata is an affiliate graduate faculty member and research consultant at the University of Hawai’i at Manoa. Her research interests focus on faculty, distance learning, and technology issues in higher education.