Inference and Diagnostics for Respondent-Driven Sampling Data

03/15/2016 - 15:30
03/15/2016 - 16:30
Krista J. Gile, University of Massachusetts
Purvis Hall, 1020 Pine Ave. West, Room 24

 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, which complicate inference. In this talk, I highlight key methodological challenges arising from data collected in this manner. I then introduce key methods for diagnostics and inference in these settings, and describe new methods under development.

Last edited by on Thu, 03/10/2016 - 15:54