Applied latent class analysis /

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Bibliographic Details
Imprint:	Cambridge ; New York : Cambridge University Press, 2002.
Description:	1 online resource (xxii, 454 pages) : illustrations
Language:	English
Subject:	Latent structure analysis. Latent variables. Statistics Latent structure analysis. Latent variables. Electronic books.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11144656

Hidden Bibliographic Details
Other authors / contributors:	Hagenaars, Jacques A. McCutcheon, Allan L., 1950-2016.
ISBN:	0511065949 9780511065941 0511068077 9780511068072 0511059639 9780511059636 9780511499531 0511499531 1280417269 9781280417269 0521594510 9780521594516 1107127556 9781107127555 9786610417261 6610417261 1139145630 9781139145633 0511180675 9780511180675 0511326408 9780511326400 0521594510 9780521594516 9780521104050 052110405X
Digital file characteristics:	data file
Notes:	Includes bibliographical references and indexes. English. Print version record.
Summary:	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.
Other form:	Print version: Applied latent class analysis. Cambridge ; New York : Cambridge University Press, 2002
Standard no.:	9780521594516

Table of Contents:

Preface
Part I. Introduction
1. Latent class analysis
2. Basic concepts and procedures in singe- and multiple-group latent class analysis
Part II. Classification and Measurement
3. Latent class cluster analysis
4. Some examples of latent budget analysis and its extensions
5. Ordering the classes
6. Comparison and choice
7. Three-parameter linear logistic latent class analysis
Part III.
8. Use of categorical and continuous covariates in latent class analysis
9. Directed loglinear modelling with latent variables
10. Latent class models for longitudinal data
11. Latent markov chains
Part IV. Unobserved heterogeneity and non-response
12. A latent class approach to measuring the fit of a statistical model
13. Mixture regression models
14. A general latent class approach to unobserved heterogeneity in the analysis of event history data
15. Latent class models for contingency tables with missing data
Appendices
Index

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