Population size estimation with interval censored counts and external information: Prevalence of multiple sclerosis in Rome.

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ID: 84568
2020
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Abstract
We discuss Bayesian log-linear models for incomplete contingency tables with both missing and interval censored cells, with the aim of obtaining reliable population size estimates. We also discuss use of external information on the censoring probability, which may substantially reduce uncertainty. We show in simulation that information on lower bounds and external information can each improve the mean squared error of population size estimates, even when the external information is not completely accurate. We conclude with an original example on estimation of prevalence of multiple sclerosis in the metropolitan area of Rome, where five out of six lists have interval censored counts. External information comes from mortality rates of multiple sclerosis patients.
Reference Key
farcomeni2020populationbiometrical Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Farcomeni, Alessio;
Journal biometrical journal biometrische zeitschrift
Year 2020
DOI
10.1002/bimj.201900268
URL
Keywords
capture-recapture external information incomplete tables left-censored counts right-censored counts

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