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Epidemiological models for a Respondent Driven Sample

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If you have a question about this talk, please contact Nikolaos Demiris.

Researchers studying hidden populations (such as injecting drug users) are often using chain-referral sampling schemes – snowball sampling or respondent driven sampling (RDS). Estimation and inference based on a chain-referral sample is not trivial, since the observations are likely to be correlated – friends tend to be more similar to each other than just two randomly selected persons from target population. There also exists sampling bias, because some people have higher probability of being sampled. Despite the obvious difficulties, more than 100 studies in recent years have used RDS . In the talk, some likelihood-based methods will be proposed for analysing datasets collected by RDS , to make valid inferences for the parameters of interest.

This talk is part of the MRC Biostatistics Unit Seminars series.

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