Applied Latent Class Analysis
Published on 24. June 2002
Book
Hardback
480 pages
978-0-521-59451-6 (ISBN)
Description
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.
More details
Language
English
Place of publication
Cambridge
United Kingdom
Target group
Professional and scholarly
College/higher education
Illustrations
118 Tables, unspecified; 34 Line drawings, unspecified
Dimensions
Height: 235 mm
Width: 157 mm
Thickness: 33 mm
Weight
924 gr
ISBN-13
978-0-521-59451-6 (9780521594516)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions
Jacques A. Hagenaars | Allan L. McCutcheon
Applied Latent Class Analysis
E-Book
12/2004
1st Edition
Cambridge University Press
€50.49
Available for download
Persons
Content
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.