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Population size estimation in a two-list surveillance system with a discrete covariate
1Department of Statistics, University of California, Riverside, California 92521, USA.
Abstract:
Capture-recapture methods are widely adopted to estimate sizes of populations of public health interest using information from surveillance systems. For a two-list surveillance system with a discrete covariate, a population is divided into several subpopulations. A unified framework is proposed in which the logits of presence probabilities are decomposed into case effects and list effects. The estimators for the whole population and subpopulation sizes, their adjusted versions, and asymptotic standard errors admit closed-form expressions. Asymptotic and bootstrap individual and simultaneous confidence intervals are easily constructed. Conditional likelihood ratio tests are used to select one from three possible models. Real examples are investigated.
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