Work

Population Size Estimation Using Multiple Respondent-Driven Sampling Surveys

Year: 2019

Type: article

Abstract: Respondent-driven sampling (RDS) is commonly used to study hard-to-reach populations since traditional methods are unable to efficiently survey members due to the typically highly stigmatized nature of the population. The number of people in these populations is of primary global health and demographic interest and is usually hard to estimate. However, due to the nature of RDS, current methods of population size estimation are insufficient. We introduce a new method of estimating population size that uses concepts from capture-recapture methods while modeling RDS as a successive sampling process. We assess its statistical validity using information from the CDC's National HIV Behavioral Surveillance system in 2009 and 2012.

Source: Journal of Survey Statistics and Methodology

DOI: 10.1093/jssam/smz055

Authors: Brian J Kim, Mark S Handcock

Institutions: University of Maryland, College Park, University of California, Los Angeles

Language: English

Topic: Census and Population Estimation

Subfield: Statistics and Probability

Field: Mathematics

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Science Foundation, National Institute of Child Health and Human Development, Eunice Kennedy Shriver National Institute of Child Health and Human Development