Evidence map›Paper›PMID 41815788›Full record

ArticleSurvey research methods2025

Measuring Network Sizes in the Context of Respondent Driven Sampling: Evidence from Two Independent Surveys.

Sunghee Lee, Jacob Fisher, Ai Rene Ong, Michael Elliott, Kaidar Nurumov, Jinseok Kim

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Survey research methods, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Sunghee LeeUniversity of Michigan, Institute for Social Research.
Jacob FisherUniversity of Michigan, Institute for Social Research.
Ai Rene OngAmerican Institutes for Research.
Michael ElliottUniversity of Michigan, Institute for Social Research.
Kaidar NurumovUniversity of Michigan, Institute for Social Research.
Jinseok KimUniversity of Michigan, Institute for Social Research.

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

Social networks are the fundamental premise of respondent driven sampling (RDS). Personal network sizes termed as "degrees" play an important role in the RDS literature, as RDS-specific point estimators incorporate degrees as an adjustment factor approximating the selection probabilities. For this reason, degrees relevant to RDS should consider

Indexed as

measurement errornetwork size measurementquestion wordingrespondent driven sampling

Identifiers

PMID41815788
PMCPMC12975104

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.