Generalized least squares can overcome the critical threshold in respondent-driven sampling

Abstract

Respondent-driven sampling (RDS) is a popular technique to sample marginalized or hard-to-reach populations, where participants can refer multiple contacts into the sample. Using the sampled participants, we wish to estimate properties of the population, often the proportion of individuals that are HIV+. Because contacts often share the same HIV status, adjacent samples are dependent. As a result, RDS can lead to highly variable estimates of HIV prevalence. This paper studies an estimation technique for HIV prevalence that is based upon the classical idea of generalized least squares.

Document Details

• Document Type: Pub Defense Publication
• Publication Date: Sep 25, 2018
• Source ID: 10.1073/pnas.1706699115

Entities

People

• Karl Rohe
• Sebastien Roch

Organizations

• Army Research Office
• National Science Foundation
• University of Wisconsin–Madison

Tags

Fields of Study

• Mathematics

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