Spatial Recruitment Bias in Respondent-Driven Sampling: Implications for HIV Prevalence Estimation in Urban Heterosexuals

Samuel M. Jenness, Alan Neaigus, Travis Wendel, Camila Gelpi-Acosta, Holly Hagan

Research output: Contribution to journalArticle

Abstract

Respondent-driven sampling (RDS) is a study design used to investigate populations for which a probabilistic sampling frame cannot be efficiently generated. Biases in parameter estimates may result from systematic non-random recruitment within social networks by geography. We investigate the spatial distribution of RDS recruits relative to an inferred social network among heterosexual adults in New York City in 2010. Mean distances between recruitment dyads are compared to those of network dyads to quantify bias. Spatial regression models are then used to assess the impact of spatial structure on risk and prevalence outcomes. In our primary distance metric, network dyads were an average of 1.34 (95 % CI 0.82–1.86) miles farther dispersed than recruitment dyads, suggesting spatial bias. However, there was no evidence that demographic associations with HIV risk or prevalence were spatially confounded. Therefore, while the spatial structure of recruitment may be biased in heterogeneous urban settings, the impact of this bias on estimates of outcome measures appears minimal.

Original languageEnglish (US)
Pages (from-to)2366-2373
Number of pages8
JournalAIDS and Behavior
Volume18
Issue number12
DOIs
StatePublished - Dec 1 2014

Fingerprint

Heterosexuality
Social Support
HIV
Geography
Demography
Outcome Assessment (Health Care)
Population
Surveys and Questionnaires
Spatial Regression

Keywords

  • Heterosexual
  • HIV/AIDS
  • Respondent-driven sampling
  • Survey sampling

ASJC Scopus subject areas

  • Public Health, Environmental and Occupational Health
  • Infectious Diseases
  • Social Psychology

Cite this

Spatial Recruitment Bias in Respondent-Driven Sampling : Implications for HIV Prevalence Estimation in Urban Heterosexuals. / Jenness, Samuel M.; Neaigus, Alan; Wendel, Travis; Gelpi-Acosta, Camila; Hagan, Holly.

In: AIDS and Behavior, Vol. 18, No. 12, 01.12.2014, p. 2366-2373.

Research output: Contribution to journalArticle

Jenness, Samuel M. ; Neaigus, Alan ; Wendel, Travis ; Gelpi-Acosta, Camila ; Hagan, Holly. / Spatial Recruitment Bias in Respondent-Driven Sampling : Implications for HIV Prevalence Estimation in Urban Heterosexuals. In: AIDS and Behavior. 2014 ; Vol. 18, No. 12. pp. 2366-2373.
@article{31179266b53d4a66ae65584c92eaf82d,
title = "Spatial Recruitment Bias in Respondent-Driven Sampling: Implications for HIV Prevalence Estimation in Urban Heterosexuals",
abstract = "Respondent-driven sampling (RDS) is a study design used to investigate populations for which a probabilistic sampling frame cannot be efficiently generated. Biases in parameter estimates may result from systematic non-random recruitment within social networks by geography. We investigate the spatial distribution of RDS recruits relative to an inferred social network among heterosexual adults in New York City in 2010. Mean distances between recruitment dyads are compared to those of network dyads to quantify bias. Spatial regression models are then used to assess the impact of spatial structure on risk and prevalence outcomes. In our primary distance metric, network dyads were an average of 1.34 (95 {\%} CI 0.82–1.86) miles farther dispersed than recruitment dyads, suggesting spatial bias. However, there was no evidence that demographic associations with HIV risk or prevalence were spatially confounded. Therefore, while the spatial structure of recruitment may be biased in heterogeneous urban settings, the impact of this bias on estimates of outcome measures appears minimal.",
keywords = "Heterosexual, HIV/AIDS, Respondent-driven sampling, Survey sampling",
author = "Jenness, {Samuel M.} and Alan Neaigus and Travis Wendel and Camila Gelpi-Acosta and Holly Hagan",
year = "2014",
month = "12",
day = "1",
doi = "10.1007/s10461-013-0640-8",
language = "English (US)",
volume = "18",
pages = "2366--2373",
journal = "AIDS and Behavior",
issn = "1090-7165",
publisher = "Springer New York",
number = "12",

}

TY - JOUR

T1 - Spatial Recruitment Bias in Respondent-Driven Sampling

T2 - Implications for HIV Prevalence Estimation in Urban Heterosexuals

AU - Jenness, Samuel M.

AU - Neaigus, Alan

AU - Wendel, Travis

AU - Gelpi-Acosta, Camila

AU - Hagan, Holly

PY - 2014/12/1

Y1 - 2014/12/1

N2 - Respondent-driven sampling (RDS) is a study design used to investigate populations for which a probabilistic sampling frame cannot be efficiently generated. Biases in parameter estimates may result from systematic non-random recruitment within social networks by geography. We investigate the spatial distribution of RDS recruits relative to an inferred social network among heterosexual adults in New York City in 2010. Mean distances between recruitment dyads are compared to those of network dyads to quantify bias. Spatial regression models are then used to assess the impact of spatial structure on risk and prevalence outcomes. In our primary distance metric, network dyads were an average of 1.34 (95 % CI 0.82–1.86) miles farther dispersed than recruitment dyads, suggesting spatial bias. However, there was no evidence that demographic associations with HIV risk or prevalence were spatially confounded. Therefore, while the spatial structure of recruitment may be biased in heterogeneous urban settings, the impact of this bias on estimates of outcome measures appears minimal.

AB - Respondent-driven sampling (RDS) is a study design used to investigate populations for which a probabilistic sampling frame cannot be efficiently generated. Biases in parameter estimates may result from systematic non-random recruitment within social networks by geography. We investigate the spatial distribution of RDS recruits relative to an inferred social network among heterosexual adults in New York City in 2010. Mean distances between recruitment dyads are compared to those of network dyads to quantify bias. Spatial regression models are then used to assess the impact of spatial structure on risk and prevalence outcomes. In our primary distance metric, network dyads were an average of 1.34 (95 % CI 0.82–1.86) miles farther dispersed than recruitment dyads, suggesting spatial bias. However, there was no evidence that demographic associations with HIV risk or prevalence were spatially confounded. Therefore, while the spatial structure of recruitment may be biased in heterogeneous urban settings, the impact of this bias on estimates of outcome measures appears minimal.

KW - Heterosexual

KW - HIV/AIDS

KW - Respondent-driven sampling

KW - Survey sampling

UR - http://www.scopus.com/inward/record.url?scp=84963952318&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84963952318&partnerID=8YFLogxK

U2 - 10.1007/s10461-013-0640-8

DO - 10.1007/s10461-013-0640-8

M3 - Article

C2 - 24122043

AN - SCOPUS:84963952318

VL - 18

SP - 2366

EP - 2373

JO - AIDS and Behavior

JF - AIDS and Behavior

SN - 1090-7165

IS - 12

ER -