2010/12/18 by Amber Tomas, Tomas, Amber, Krista J. Gile +1
Mathematics · #62P25 #Applications (stat.AP) #FOS: Computer and information sciences #msc:62P25 #stat.AP
paper · pdf · doi:10.48550/arxiv.1012.4122
26 pages, 13 figures
arxiv created 2010/12/18 · arxiv updated 2010/12/21
Respondent-driven sampling is a widely-used network sampling technique, designed to sample from hard-to-reach populations. Estimation from the resulting samples is an area of active research, with software available to compute at least four estimators of a population proportion. Each estimator is claimed to address deficiencies in previous estimators, however those claims are often unsubstantiated. In this study we provide a simulation-based comparison of five existing estimators, focussing on sampling conditions which a recent estimator is designed to address. We find no estimator consistently out-performs all others, and highlight sampling conditions in which each is to be preferred.