On the Estimation of Homogeneous Population Size in a Complex Dual-record System

Abstract

Dual-record system (DRS) (equivalently two sample Capture-recapture experiment) model with time and behavioral response variation, has attracted much attention specifically in the domain of Official Statistics and Epidemiology. The relevant model suffers from parameter identifiability problem and proper Bayesian methodologies could be helpful to overcome the situation. In this article, we have formulated the population size estimation problem in DRS as a missing data analysis under both the known and unknown directional nature of underlying behavioral response effect. Two simple empirical Bayes approaches are proposed and investigated their performances for this complex model along with a fully Bayes treatment. Extensive simulation studies are carried out to compare the performances of these competitive approaches and a real data example is also illustrated. Finally, some features of these methods and recommendations to implement them in practice are explored depending upon the availability of knowledge on the nature of behavioral response effect.

25 pages, 3 figures

References in corpus (1)

• Bayesian shrinkage methods for partially observed data with many predictors

Cited by in corpus (4)

• A new integrated likelihood for estimating population size in dependent dual-record system
• Tailoring Capture-Recapture Methods to Estimate Registry-Based Case Counts Based on Error-Prone Diagnostic Signals
• On the Estimation of Population Size from a Dependent Triple Record System
• On the Population Size Estimation from Dual-record System: Profile-Likelihood Approaches