This study 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 the volume, each presenting a key innovation to the basic LCM and illustrating how it can prove useful in situations typically encountered in actual research.
Contents
Preface Jacques A. Hagenaars and Allan L. McCutcheon; Part I. Introduction: 1. Latent class analysis Leo A. Goodman; 2. Basic concepts and procedures in singe- and multiple-group latent class analysis Allan L. McCutcheon; Part II. Classification and Measurement: 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 Ulf Bockenholt; 7. Three-parameter linear logistic latent class analysis Anton K. Formann and Thomas Kohlmann; Part III. 8. Use of categorical and continuous covariates in latent class analysis C. Mitchell Dayton and George B. Macready; 9. Directed loglinear modelling with latent variables 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; Part IV. Unobserved heterogeneity and non-response: 12. A latent class approach to measuring the fit of a statistical model Tamas Rudas; 13. Mixture regression models Michael 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; Appendices; Index.
Printer friendly version
Email a colleague