A latent class approach with covariates and local dependence in capture-recapture models

Thandrayen, J and Wang, Y 2013, 'A latent class approach with covariates and local dependence in capture-recapture models', Advances and Applications in Statistics, vol. 34, no. 1, pp. 65-84.


Document type: Journal Article
Collection: Journal Articles

Title A latent class approach with covariates and local dependence in capture-recapture models
Author(s) Thandrayen, J
Wang, Y
Year 2013
Journal name Advances and Applications in Statistics
Volume number 34
Issue number 1
Start page 65
End page 84
Total pages 20
Publisher Pushpa Publishing House
Abstract Traditional capture-recapture methods assume that lists operate independently (local independence) and that capture probabilities are homogeneous. In studies involving human populations, these assumptions are often violated. This paper presents an approach where dependence between the lists and the effects due to the observable covariates are modelled directly in the capture probability. For this purpose, we employ a multinomial latent class model. Estimation of the model parameters is based on the maximum likelihood method via the EM algorithm. An approximation for the variance of the unknown population size is also formulated.
Subject Statistical Theory
Keyword(s) conditional likelihood
covariate
EM algorithm
heterogeneity
latent class model
multinomial logit
Copyright notice © 2013 Pushpa Publishing House
ISSN 0972-3617
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