Premium
Population size estimation with interval censored counts and external information: Prevalence of multiple sclerosis in Rome
Author(s) -
Farcomeni Alessio
Publication year - 2020
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.201900268
Subject(s) - censoring (clinical trials) , statistics , contingency table , population , estimation , interval estimation , prediction interval , bayes' theorem , bayesian probability , mathematics , confidence interval , interval (graph theory) , demography , management , combinatorics , economics , sociology
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.