Latent class analysis of two-way contingency tables by Bayesian methods

Latent class analysis in two-way contingency tables usually suffers from unidentifiability problems. These an be overcome by using Bayesian techniques in which prior distributions are assumed on the latent parameters. Application of these techniques, however, involves some unusual computational diff...

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Bibliographic Details
Published in:Biometrika 1989-09, Vol.76 (3), p.557-563
Main Authors: EVANS, MICHAEL J., GILULA, ZVI, GUTTMAN, IRWIN
Format: Article
Language:English
Subjects:
Adaptive importance sampling
Analytical estimating
Bayes estimators
Bayesian estimation
Computer analysis
Contingency table
Dirichlet prior
Estimators for the mean
Exact sciences and technology
Latent class model
Length of stay
Mathematical independent variables
Mathematics
Probability and statistics
Random variables
Sample size
Sciences and techniques of general use
Statistical discrepancies
Statistics
Stochastic models
Citations: Items that cite this one
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Description
Summary:Latent class analysis in two-way contingency tables usually suffers from unidentifiability problems. These an be overcome by using Bayesian techniques in which prior distributions are assumed on the latent parameters. Application of these techniques, however, involves some unusual computational difficulties. Bayesian techniques suitable for latent class analyses together with a remedy to the computational difficulties are discussed in this paper.
ISSN:0006-3444
1464-3510
DOI:10.1093/biomet/76.3.557