Exploring Mechanisms of Recruitment and Recruitment Cooperation in Respondent Driven Sampling.

Sunghee Lee, Ai Rene Ong, Michael Elliott

Abstract read

In one paragraph

Article in Journal of official statistics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it

0cells of the map it votes in

4citing papers in PubMed

–field-weighted citation impact

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

4 citing papers in PubMed.

A Latent Variable Model for Individual Degree Measures in Respondent-Driven Sampling.Journal of the American Statistical Association · 2025
Article
Measuring Network Sizes in the Context of Respondent Driven Sampling: Evidence from Two Independent Surveys.Survey research methods · 2025
Article
Challenges of virtual RDS for recruitment of sexual minority women for a behavioral health study.Journal of survey statistics and methodology · 2022
Article
Employing Respondent Driven Sampling (RDS) to recruit people who inject drugs (PWID) and other hard-to-reach populations during COVID-19: Lessons learned.Frontiers in psychiatry · 2022
Article

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

3 authors.

Sunghee LeeInstitute for Social Research, University of Michigan, 426 Thompson St., Ann Arbor, MI 48104, U.S.A.

Ai Rene OngInstitute for Social Research, University of Michigan, 426 Thompson St., Ann Arbor, MI 48104, U.S.A.

Michael ElliottInstitute for Social Research, University of Michigan, 426 Thompson St., Ann Arbor, MI 48104, U.S.A.

Funding

Improving Reproducibility of Respondent Driven Sampling through Adaptive Design - Diversity SupplementR01AG060936 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LEE, SUNG-HEE · 2019 to 2023

$2.2M

Exploring Design Aspects of Web-Based Respondent-Driven Sampling for Racial/Ethnic MinoritiesR21AG062844 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI LEE, SUNG-HEE · 2019 to 2020

$429k

NIA NIH HHS R01 AG060936NIA NIH HHS R21 AG062844

6 · The paper itself

Abstract

Respondent driven sampling (RDS) is a sampling method designed for hard-to-sample groups with strong social ties. RDS starts with a small number of arbitrarily selected participants ("

Indexed as

nonresponse errorRespondent driven samplingsampling hard-to-reach population

Identifiers

PMID33162642

DOI10.2478/jos-2020-0018

PMCPMC7643877

What OpenQuestion holds

Textmetadata

LicenceTDM

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.