Network model-assisted inference from respondent-driven sampling data
نویسندگان
چکیده
منابع مشابه
Network Model-Assisted Inference from Respondent-Driven Sampling Data.
Respondent-Driven Sampling is a widely-used method for sampling hard-to-reach human populations by link-tracing over their social networks. Inference from such data requires specialized techniques because the sampling process is both partially beyond the control of the researcher, and partially implicitly defined. Therefore, it is not generally possible to directly compute the sampling weights ...
متن کاملRespondent Driven Sampling
Respondent driven sampling (RDS) is a network sampling technique typically employed for hard-to-reach populations (e.g. drug users, men who have sex with men, people with HIV). Similar to snowball sampling, initial seed respondents recruit additional respondents from their network of friends. The recruiting process repeats iteratively, thereby forming long referral chains. Unlike in snowball sa...
متن کاملRandom Walks on Directed Networks: Inference and Respondent-driven Sampling
Respondent driven sampling (RDS) is a method often used to estimate population properties (e.g. sexual risk behavior) in hard-to-reach populations. It combines an effective modified snowball sampling methodology with an estimation procedure that yields unbiased population estimates under the assumption that the sampling process behaves like a random walk on the social network of the population....
متن کاملAssessing respondent-driven sampling.
Respondent-driven sampling (RDS) is a network-based technique for estimating traits in hard-to-reach populations, for example, the prevalence of HIV among drug injectors. In recent years RDS has been used in more than 120 studies in more than 20 countries and by leading public health organizations, including the Centers for Disease Control and Prevention in the United States. Despite the widesp...
متن کاملInference for the Visibility Distribution for Respondent-Driven Sampling
Respondent-Driven Sampling (RDS) is used throughout the world to estimate prevalences and population sizes for hard-to-reach populations. Although RDS is an effective method for enrolling people from key populations (KPs) in studies, it relies on an unknown sampling mechanism and thus each individual’s inclusion probability is unknown. Current estimators rely on a participant’s network size (de...
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ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series A (Statistics in Society)
سال: 2015
ISSN: 0964-1998
DOI: 10.1111/rssa.12091