Capture-recapture analysis with a latent class model allowing for local dependence and observed heterogeneity

Thandrayen, J and Wang, Y 2010, 'Capture-recapture analysis with a latent class model allowing for local dependence and observed heterogeneity', Biometrical Journal: journal of mathematical methods in biosciences, vol. 52, no. 4, pp. 552-561.


Document type: Journal Article
Collection: Journal Articles

Title Capture-recapture analysis with a latent class model allowing for local dependence and observed heterogeneity
Author(s) Thandrayen, J
Wang, Y
Year 2010
Journal name Biometrical Journal: journal of mathematical methods in biosciences
Volume number 52
Issue number 4
Start page 552
End page 561
Total pages 10
Publisher Wiley - V C H Verlag GmbH & Co. KGaA
Abstract In epidemiology, capture-recapture models are commonly used to estimate the size of an unknown population based on several incomplete lists of individuals. The method operates under two main assumptions: independence between the lists (local independence) and homogeneity of capture probabilities of individuals. In practice, these assumptions are rarely satisfied. We introduce a multinomial latent class model that can account for both list dependence and heterogeneity. Parameter estimation is performed by maximizing the conditional likelihood function with the use of the EM algorithm. In addition, a new approach for evaluating the standard errors of the parameter estimates is discussed, which considerably reduces the computational burden associated with the evaluation of the variance of the population size estimate.
Subject Statistics not elsewhere classified
Keyword(s) Record Systems Estimation
Variable Regression
Closed Populations
Ascertainment
Size
DOI - identifier 10.1002/bimj.200900051
Copyright notice © Wiley-V C H Verlag Gmbh
ISSN 0323-3847
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Citation counts: TR Web of Science Citation Count  Cited 7 times in Thomson Reuters Web of Science Article | Citations
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