Abstract Details
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Activity Number:
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668
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Type:
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Topic Contributed
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Date/Time:
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Thursday, August 8, 2013 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistics in Epidemiology
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| Abstract - #309397 |
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Title:
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Advances in Model-Assisted Inference from Respondent-Driven Sampling Data
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Author(s):
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Krista J. Gile*+
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Companies:
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University of Massachusetts, Amherst
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Keywords:
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respondent-driven sampling ;
network ;
network sampling ;
survey sampling ;
link-tracing ;
hard-to-reach
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Abstract:
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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 effected by many features of the network and sampling process. In this paper, we present advances in inference that adjust for many such features, which induce bias in earlier estimators.
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Authors who are presenting talks have a * after their name.
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