On the estimation of population size from a post-stratified two-sample capture–recapture data under dependence

ABSTRACT

Population size estimation based on a two-sample capture–recapture type experiment is an interesting problem in various fields including epidemiology, public health, population studies, etc. The Lincoln–Petersen estimate is popularly used under the assumption that the capture and recapture statuses of each individual is independent. However, in many real-life scenarios, there is an inherent dependency between capture and recapture attempts which is not well studied in the literature of the dual system or two-sample capture–recapture method. In this article, we propose a novel model that successfully incorporates the possible causal dependency and provide corresponding estimation methodologies for the associated model parameters based on post-stratified two-sample capture–recapture data. The superiority of the performance of the proposed model over the existing competitors is established through an extensive simulation study. The method is illustrated through analyses of some real data sets.

KEYWORDS:

• Behavioural dependency
• bivariate Bernoulli
• disease surveillance
• method of moments
• maximum likelihood
• post-stratification

Acknowledgment

The authors are thankful to Prof. Anup Dewanji and Prof. Murari Mitra for many helpful comments and suggestions.

Disclosure statement

No potential conflict of interest was reported by the authors.

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.