Applied Latent Class Analysis (eBook, PDF)

Redaktion: Hagenaars, Jacques A.

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Cambridge University Press
• Erscheinungstermin: 24. Juni 2002
• Englisch
• ISBN-13: 9780511059636
• Artikelnr.: 38189172

Inhaltsangabe

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.