Categorical Data Analysis with Structural Equation Models

Applications in Mplus and lavaan

Kevin J Grimm author

Format:Hardback

Publisher:Guilford Publications

Publishing:22nd Oct '25

£62.99

This title is due to be published on 22nd October, and will be despatched as soon as possible.

Categorical Data Analysis with Structural Equation Models cover

Multivariate categorical outcomes, such as Likert scale responses and disease diagnoses, require specialized structural equation modeling (SEM) software to be analyzed properly. Providing needed skills for applied researchers and graduate students, this book leads readers from regression analysis with categorical outcomes to complex SEMs with latent variables for categorical indicators. The initial section sets the stage by demonstrating regression analyses for binary, ordered, or count outcomes using R. Chapters then reanalyze the same data using Mplus and R lavaan to show how univariate models for categorical outcomes can be estimated and interpreted with SEM programs. Subsequently, the book turns to multivariate models, discussing path models, confirmatory factor models, and latent variable path models with categorical outcomes. Concluding chapters cover advanced SEM with categorical outcomes, including growth models, latent class models, and survival models. Worked-through examples featured throughout. The companion website provides R (including lavaan), Mplus, and SAS code, as applicable, for the examples.

“Grimm once again shows his knack for taking complex statistical models and ideas and expressing them in understandable terms. Categorical data come in many forms: binary, ordinal, and count variables, among others. Grimm explains modeling options for each type of analytic model, from regression models to more advanced models. Example scripts for Mplus and lavaan provide readers with clear roadmaps for conducting analyses and understanding results. This book is a ‘must read’ for anyone interested in learning about categorical data analysis in the social sciences using state-of-the-art methods.”--Keith F. Widaman, PhD, Distinguished Professor Emeritus of Education and Distinguished Professor of the Graduate Division, University of California, Riverside

"This book fills an important gap in texts on SEM. Grimm provides rigorous, in-depth coverage of regression, path models, SEM, growth models, and mixture models, combined with practical instruction on programming in Mplus and lavaan. This book is a valuable resource for researchers modeling categorical, count, and time-to-event data, frequently encountered in social science research. As a course text, this book will provide the next level of knowledge to students who have learned the basics of SEM, and it will equip them with the expertise and skills necessary to implement these sophisticated models."--Paul Sacco, PhD, School of Social Work, University of Maryland, Baltimore

“This book offers comprehensive coverage of key topics in SEM with categorical data. Chapters include practical data analysis examples using two widely adopted SEM software packages--Mplus and R (with the lavaan package)--accompanied by clear interpretations of the results. I highly recommend this book to researchers seeking to deepen their understanding of categorical data analysis in applied contexts. It also serves as an excellent text for graduate-level courses on categorical data analysis and advanced SEM.”--Myeongsun Yoon, PhD, Department of Educational Psychology, Texas A&M University

“I particularly enjoy the lavaan and Mplus code that accompanies the book, which is more detailed than in other books I have come across. The book is well written and provides excellent syntax examples. I would use it to teach categorical SEM in my graduate SEM course.”--Jam Khojasteh, PhD, Research, Evaluation, Measurement, and Statistics Program, Oklahoma State University-

ISBN: 9781462558315

Dimensions: unknown

Weight: unknown

368 pages