Nonparametric Identification for Respondent-Driven Sampling

Peter M Aronow; Forrest W Crawford

doi:10.1016/j.spl.2015.07.003

Nonparametric Identification for Respondent-Driven Sampling

Stat Probab Lett. 2015 Nov 1:106:100-102. doi: 10.1016/j.spl.2015.07.003.

Authors

Peter M Aronow¹, Forrest W Crawford²

Affiliations

¹ Department of Political Science, Yale University ; Department of Biostatistics, Yale School of Public Health.
² Department of Biostatistics, Yale School of Public Health.

Abstract

We detail nonparametric identification results for respondent-driven sampling when sampling probabilities are assumed to be functions of network degree known to scale. We show that the conditions for consistency of the Volz-Heckathorn estimator are weaker than previously assumed.

Keywords: Horvitz-Thompson estimator; network degree; respondent-driven sampling.

Abstract

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