Unweighted regression models perform better than weighted regression techniques for respondent-driven sampling data: results from a simulation study.

ABSTRACT:

Background

It is unclear whether weighted or unweighted regression is preferred in the analysis of data derived from respondent driven sampling. Our objective was to evaluate the validity of various regression models, with and without weights and with various controls for clustering in the estimation of the risk of group membership from data collected using respondent-driven sampling (RDS).

Methods

Twelve networked populations, with varying levels of homophily and prevalence, based on a known distribution of a continuous predictor were simulated using 1000 RDS samples from each population. Weighted and unweighted binomial and Poisson general linear models, with and without various clustering controls and standard error adjustments were modelled for each sample and evaluated

SUBMITTER: Avery L 

PROVIDER: S-EPMC6819607 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature