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

Title: A latent class approach with covariates and local dependence in capture-recapture models
Creator: Thandrayen, Joanne; Wang, Yan
Relation: Advances and Applications in Statistics Vol. 34, Issue 1, p. 65-84
Relation: http://www.pphmj.com/journals/articles/1085.htm
Publisher: Pushpa Publishing
Resource Type: journal article
Date: 2013
Description: 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: conditional likelihood; covariate; EM algorithm; heterogeneity; latent class model; multinomial logit
Identifier: http://hdl.handle.net/1959.13/1317597
Identifier: uon:23448
Identifier: ISSN:0972-3617
Language: eng
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