Format

Send to

Choose Destination
See comment in PubMed Commons below
Am J Epidemiol. 2017 Jun 9. doi: 10.1093/aje/kwx208. [Epub ahead of print]

Identification of homophily and preferential recruitment in respondent-driven sampling.

Author information

1
Department of Biostatistics, Yale School of Public Health.
2
Yale School of Management.
3
Department of Ecology & Evolutionary Biology.
4
Department of Political Science, Yale University.
5
Institute for Community Researchx.

Abstract

Respondent-driven sampling (RDS) is a link-tracing procedure used in epidemiological research on hidden or hard-to-reach populations in which subjects recruit others via their social network. Estimates from RDS studies may have poor statistical properties due to statistical dependence in sampled subjects' traits. Two distinct mechanisms account for dependence in an RDS study: homophily, the tendency for individuals to share social ties with others exhibiting similar characteristics, and preferential recruitment, in which recruiters do not recruit uniformly at random from their network alters. The different effects of network homophily and preferential recruitment in RDS studies have been a source of confusion and controversy in methodological and empirical research in epidemiology. In this paper, we give formal definitions of homophily and preferential recruitment and show that neither is identified in typical RDS studies. We derive nonparametric identification regions for homophily and preferential recruitment and show that these parameters are not identified unless the network takes a degenerate form. The results indicate that claims of homophily or recruitment bias measured from empirical RDS studies may not be credible. We apply our identification results to a study involving both a network census and RDS on a population of injection drug users in Hartford, Connecticut.

KEYWORDS:

hidden population; link-tracing; network sampling; nonparametric bounds; social network

PMID:
28605424
DOI:
10.1093/aje/kwx208
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Silverchair Information Systems
    Loading ...
    Support Center