Description

Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. Applied Latent Class Analysis introduces several 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 contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research. Applied Latent Class Analysis introduces several 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 contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research. Applied Latent Class Analysis introduces several 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 contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research. 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.