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Activity Number: 416 - Nonresponse Errors and Fixes
Type: Contributed
Date/Time: Tuesday, July 30, 2019 : 2:00 PM to 3:50 PM
Sponsor: Survey Research Methods Section
Abstract #306374 Presentation
Title: Population Size Estimation Using Multiple Respondent-Driven Sampling Surveys
Author(s): Brian Kim* and Mark Handcock
Companies: University of Maryland, College Park and University of California, Los Angles
Keywords: Hard-to-reach population sampling; Network Sampling; Model-based survey sampling; Capture-Recapture; Probability proportional to size without replacement sampling

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.

Authors who are presenting talks have a * after their name.

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