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The Use of Mixed Logit Models to Reflect Heterogeneity in Capture‐Recapture Studies
Author(s) -
Coull Brent A.,
Agresti Alan
Publication year - 1999
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/j.0006-341x.1999.00294.x
Subject(s) - statistics , econometrics , mixed logit , logit , mark and recapture , mathematics , homogeneity (statistics) , logistic regression , mixed model , generalized linear mixed model , random effects model , log linear model , population , linear model , medicine , demography , meta analysis , sociology
Summary. 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.