Abstract Details
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Activity Number:
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574
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Type:
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Contributed
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Date/Time:
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Wednesday, August 6, 2014 : 2:00 PM to 3:50 PM
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Sponsor:
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Section on Statistics in Epidemiology
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Abstract #313382
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Title:
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Edge Sampling Probabilities in Respondent-Driven Sampling
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Author(s):
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Miles Ott*+ and Krista J. Gile and Joseph Hogan and Matthew T. Harrison
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Companies:
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Augsburg College and University of Massachusetts, Amherst and Brown University and Brown University
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Keywords:
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Respondent-Driven Sampling ;
network sampling ;
social networks ;
hard to reach populations
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Abstract:
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Respondent-Driven Sampling (RDS) is a commonly used link-tracing sampling design for samples of populations for which there is no available sampling frame. RDS estimators rely upon the assumption that each edge (representing a relationship between two individuals) in the underlying network of relationships has an equal probability of being sampled. We show that this assumption is violated in even the simplest cases, and that current RDS estimators and diagnostics are sensitive to the violation of this assumption.
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Authors who are presenting talks have a * after their name.
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