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Activity Number: 379 - Understanding HIV/AIDS Epidemics with Newly Available Data Sources
Type: Invited
Date/Time: Tuesday, August 1, 2017 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistics in Epidemiology
Abstract #324612 View Presentation
Title: Inference from Respondent-Driven Sampling Data: Progress and Challenges
Author(s): Krista Gile* and Miles Ott and Isabelle Beaudry
Companies: University of Massachusetts and Smith College and PUC Santiago, Chile
Keywords: Respondent-driven sampling ; NMAR ; networks ; sampling ; hard-to-reach populations ; network sampling
Abstract:

Respondent-Driven Sampling is type of link-tracing network sampling used to study hard-to-reach populations. Beginning with a convenience sample, each person sampled is given 2-3 uniquely identified coupons to distribute to other members of the target population, making them eligible for enrollment in the study. This is effective at collecting large diverse samples from many populations.

Unfortunately, sampling is affected by many features of the network and sampling process, inducing a non-ignorable sampling design, and many potential biases related to network structure and recruitment behavior. In this talk, we highlight key methodological challenges arising from data collected in this manner, including both progress to date and outstanding challenges.


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

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