Cargando…
General regression methods for respondent-driven sampling data
Respondent-driven sampling is a variant of link-tracing sampling techniques that aim to recruit hard-to-reach populations by leveraging individuals’ social relationships. As such, a respondent-driven sample has a graphical component which represents a partially observed network of unknown structure....
Autores principales: | , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8424528/ https://www.ncbi.nlm.nih.gov/pubmed/34319832 http://dx.doi.org/10.1177/09622802211032713 |
_version_ | 1783749692120629248 |
---|---|
author | Yauck, Mamadou Moodie, Erica EM Apelian, Herak Fourmigue, Alain Grace, Daniel Hart, Trevor Lambert, Gilles Cox, Joseph |
author_facet | Yauck, Mamadou Moodie, Erica EM Apelian, Herak Fourmigue, Alain Grace, Daniel Hart, Trevor Lambert, Gilles Cox, Joseph |
author_sort | Yauck, Mamadou |
collection | PubMed |
description | Respondent-driven sampling is a variant of link-tracing sampling techniques that aim to recruit hard-to-reach populations by leveraging individuals’ social relationships. As such, a respondent-driven sample has a graphical component which represents a partially observed network of unknown structure. Moreover, it is common to observe homophily, or the tendency to form connections with individuals who share similar traits. Currently, there is a lack of principled guidance on multivariate modelling strategies for respondent-driven sampling to address peer effects driven by homophily and the dependence between observations within the network. In this work, we propose a methodology for general regression techniques using respondent-driven sampling data. This is used to study the socio-demographic predictors of HIV treatment optimism (about the value of antiretroviral therapy) among gay, bisexual and other men who have sex with men, recruited into a respondent-driven sampling study in Montreal, Canada. |
format | Online Article Text |
id | pubmed-8424528 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-84245282021-09-09 General regression methods for respondent-driven sampling data Yauck, Mamadou Moodie, Erica EM Apelian, Herak Fourmigue, Alain Grace, Daniel Hart, Trevor Lambert, Gilles Cox, Joseph Stat Methods Med Res Articles Respondent-driven sampling is a variant of link-tracing sampling techniques that aim to recruit hard-to-reach populations by leveraging individuals’ social relationships. As such, a respondent-driven sample has a graphical component which represents a partially observed network of unknown structure. Moreover, it is common to observe homophily, or the tendency to form connections with individuals who share similar traits. Currently, there is a lack of principled guidance on multivariate modelling strategies for respondent-driven sampling to address peer effects driven by homophily and the dependence between observations within the network. In this work, we propose a methodology for general regression techniques using respondent-driven sampling data. This is used to study the socio-demographic predictors of HIV treatment optimism (about the value of antiretroviral therapy) among gay, bisexual and other men who have sex with men, recruited into a respondent-driven sampling study in Montreal, Canada. SAGE Publications 2021-07-28 2021-10 /pmc/articles/PMC8424528/ /pubmed/34319832 http://dx.doi.org/10.1177/09622802211032713 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution 4.0 License (https://creativecommons.org/licenses/by/4.0/) which permits any use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Articles Yauck, Mamadou Moodie, Erica EM Apelian, Herak Fourmigue, Alain Grace, Daniel Hart, Trevor Lambert, Gilles Cox, Joseph General regression methods for respondent-driven sampling data |
title | General regression methods for respondent-driven sampling data |
title_full | General regression methods for respondent-driven sampling data |
title_fullStr | General regression methods for respondent-driven sampling data |
title_full_unstemmed | General regression methods for respondent-driven sampling data |
title_short | General regression methods for respondent-driven sampling data |
title_sort | general regression methods for respondent-driven sampling data |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8424528/ https://www.ncbi.nlm.nih.gov/pubmed/34319832 http://dx.doi.org/10.1177/09622802211032713 |
work_keys_str_mv | AT yauckmamadou generalregressionmethodsforrespondentdrivensamplingdata AT moodieericaem generalregressionmethodsforrespondentdrivensamplingdata AT apelianherak generalregressionmethodsforrespondentdrivensamplingdata AT fourmiguealain generalregressionmethodsforrespondentdrivensamplingdata AT gracedaniel generalregressionmethodsforrespondentdrivensamplingdata AT harttrevor generalregressionmethodsforrespondentdrivensamplingdata AT lambertgilles generalregressionmethodsforrespondentdrivensamplingdata AT coxjoseph generalregressionmethodsforrespondentdrivensamplingdata |