Since the first edition of this book was released, there have been several advances in the methodological literature that address practical challenges to applying Latent class analysis (LCA) and Latent transition analysis (LTA) in real-world data. A second edition of this book is necessary and timely so that these topics can be included. This new edition continues to provide a comprehensive introduction to LCA and LTA for categorical data. This book also continues to cover more advanced material, including multiple-group analyses and models involving covariates. The second edition provides new material on latent profile analysis (LPA) and LCA with an observed outcome. Empirical examples continue to be used frequently to illustrate and reinforce the material, and a data analyst's perspective continues to be taken throughout. This book is aimed at advanced graduate students and can be used as a textbook in a course on categorical data analysis or latent variable models. It is also suitable as an advanced introduction to LCA and LTA for scientists who wish to apply these approaches in empirical data.

This book continues to assume that readers have some familiarity with analysis of contingency tables and with logistic regression. Readers will need a background equivalent to about two semesters of graduate level statistics for the social, behavioral, or biomedical sciences.