Table of Contents

Preface / Jacques A. Hagenaars and Allan L. McCutcheon.
1. Latent Class Analysis: The Empirical Study of Latent Types, Latent Variables, and Latent Structures / Leo A. Goodman.
2. Basic Concepts and Procedures in Single- and Multiple-Group Latent Class Analysis / Allan L. McCutcheon.
3. Latent Class Cluster Analysis / Jeroen K. Vermunt and Jay Magidson.
4. Some Examples of Latent Budget Analysis and Its Extensions / Peter G.M. van der Heijden, L. Andries van der Ark and Ab Mooijaart.
5. Ordering the Classes / Marcel Croon.
6. Comparison and Choice: Analyzing Discrete Preference Data by Latent Class Scaling Models / Ulf Bockenholt.
7. Three-Parameter Linear Logistic Latent Class Analysis / Anton K. Formann and Thomas Kohlmann.
8. Use of Categorical and Continuous Covariates in Latent Class Analysis / C. Mitchell Dayton and George B. Macready.
9. Directed Loglinear Modeling with Latent Variables: Causal Models for Categorical Data with Nonsystematic and Systematic Measurement Errors / Jacques A. Hagenaars.
10. Latent Class Models for Longitudinal Data / Linda M. Collins and Brian P. Flaherty.
11. Latent Markov Chains / Rolf Langeheine and Frank van de Pol.
12. A Latent Class Approach to Measuring the Fit of a Statistical Model / Tamas Rudas.
13. Mixture Regression Models / Michel Wedel and Wayne S. DeSarbo.
14. A General Latent Class Approach to Unobserved Heterogeneity in the Analysis of Event History Data / Jeroen K. Vermunt.
15. Latent Class Models for Contingency Tables with Missing Data / Christopher Winship, Robert D. Mare and John Robert Warren. Applied Latent Class Analysis introduces several recent innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis have contributed essays to this volume, each presenting a key innovation to the basic LCM.