Population Size Estimation Using Multiple Respondent-Driven Sampling Surveys

Author:

Kim Brian J1,Handcock Mark S2

Affiliation:

1. Lecturer in the Joint Program in Survey Methodology, University of Maryland, 1218 LeFrak Hall, 7251 Preinkert Dr., College Park, MD 20742, USA

2. Professor at the University of California, 8125 Math Sciences Bldg., Box 951554, Los Angeles, CA 90095, USA

Abstract

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.

Funder

National Science Foundation

National Institute of Child Health and Human Development

Publisher

Oxford University Press (OUP)

Subject

Applied Mathematics,Statistics, Probability and Uncertainty,Social Sciences (miscellaneous),Statistics and Probability

Reference35 articles.

1. Implementation and Analysis of Respondent Driven Sampling: Lessons Learned from the Field;Abdul-Quader;Journal of Urban Health,2006

2. Implementation of Web-Based Respondent-Driven Sampling among Men Who Have Sex with Men in Vietnam;Bengtsson;PLoS ONE,2012

3. Capture-Recapture Methods and Respondent-Driven Sampling: Their Potential and Limitations;Berchenko;Sexually Transmitted Infections,2011

4. Counting Hard-to-Count Populations: The Network Scale-Up Method for Public Health;Bernard;Sexually Transmitted Infections,2010

5. HIV Infection and HIV-Associated Behaviors among Injecting Drug Users—20 Cities, United States, 2009;Morbidity and Mortality Weekly Report,2012

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