Evidence map›Paper›PMID 28605424›Full record

ArticleAmerican journal of epidemiology2018

Identification of Homophily and Preferential Recruitment in Respondent-Driven Sampling.

Forrest W Crawford, Peter M Aronow, Li Zeng, Jianghong Li

Open access · bronzeAbstract read
In one paragraph

Article in American journal of epidemiology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.3field-weighted citation impact, top 7% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 39 citations in OpenAlex.

  1. Article
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  3. Inferring bivariate associations with continuous data from studies using respondent-driven sampling.Journal of the Royal Statistical Society. Series C, Applied statistics · 2025
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  9. General regression methods for respondent-driven sampling data.Statistical methods in medical research · 2021
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  12. Causal Inference Under Interference And Network Uncertainty.Uncertainty in artificial intelligence : proceedings of the ... conference. Conference on Uncertainty in Artificial Intelligence · 2019
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Forrest W CrawfordDepartment of Biostatistics, Yale School of Public Health, New Haven, Connecticut.
Peter M AronowDepartment of Biostatistics, Yale School of Public Health, New Haven, Connecticut.
Li ZengDepartment of Biostatistics, Yale School of Public Health, New Haven, Connecticut.
Jianghong LiInstitute for Community Research, Hartford, Connecticut.
Yale University · USHartford Financial Services (United States)

Funding

Using Coincidence Analysis to Investigate Factors Affecting PrEP Initiation and Continuation in Southern ending the Epidemic CountiesP30MH062294 · NIMH · YALE UNIVERSITY · PI John Edward Pachankis · 2001 to 2026
$48.5M
Yale University Clinical and Translational Science Award ProgramKL2TR000140 · NCATS · YALE UNIVERSITY · PI SHERWIN, ROBERT S · 2012 to 2015
$2.9M
YALE BIOMEDICAL SUPERCOMPUTER: NEUROSCIENCES10RR019895 · NCRR · YALE UNIVERSITY · PI WILLIAMS, KENNETH ROBERT · 2004 to 2004
$1.6M
IDU Peer Recruitment Dynamics and Network Structure in Respondent Driven SamplingR01DA031594 · NIDA · INSTITUTE FOR COMMUNITY RESEARCH · PI LI, JIANGHONG · 2011 to 2013
$1.6M
High Performance Computing Instrumentation for Yale University Biomedical HPC CenS10RR029676 · NCRR · YALE UNIVERSITY · PI BJORNSON, ROBERT DEAN · 2011 to 2011
$588k
NCATS NIH HHS KL2 TR000140NCRR NIH HHS S10 RR019895NCRR NIH HHS S10 RR029676NIDA NIH HHS R01 DA031594NIMH NIH HHS P30 MH062294
6 · The paper itself

Abstract

Respondent-driven sampling (RDS) is a link-tracing procedure used in epidemiologic research on hidden or hard-to-reach populations in which subjects recruit others via their social networks. 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 work, we gave formal definitions of homophily and preferential recruitment and showed that neither is identified in typical RDS studies. We derived nonparametric identification regions for homophily and preferential recruitment and showed that these parameters were not identified unless the network took a degenerate form. The results indicated that claims of homophily or recruitment bias measured from empirical RDS studies may not be credible. We applied our identification results to a study involving both a network census and RDS on a population of injection drug users in Hartford, Connecticut (2012-2013).

Indexed as

Patient SelectionSocial NetworkingBiasConnecticutDrug UsersFemaleHumansMaleSampling StudiesSurveys and Questionnaireshidden populationlink-tracingnetwork samplingnonparametric boundssocial network

Identifiers

PMID28605424
PMCPMC5860647
OpenAlexW2963066987

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.