The use of mixed logit models to reflect heterogeneity in capture-recapture studies |
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Authors: | Coull B A Agresti A |
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Affiliation: | Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA. bcoull@hsph.harvard.edu |
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Abstract: | We examine issues in estimating population size N with capture-recapture models when there is variable catchability among subjects. We focus on a logistic-normal mixed model, for which the logit of the probability of capture is an additive function of a random subject and a fixed sampling occasion parameter. When the probability of capture is small or the degree of heterogeneity is large, the log-likelihood surface is relatively flat and it is difficult to obtain much information about N. We also discuss a latent class model and a log-linear model that account for heterogeneity and show that the log-linear model has greater scope. Models assuming homogeneity provide much narrower intervals for N but are usually highly overly optimistic, the actual coverage probability being much lower than the nominal level. |
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Keywords: | Generalized linear mixed model Latent class model Log-linear model Profile likelihood Quasi symmetry Rasch model |
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