Nicky McCreesh|Simon D. W. Frost|Janet Seeley|Joseph Katongole|Matilda Nadagire Tarsh|Richard Ndunguse|F Jichi|Natasha L Lunel|Dermot Maher|Lisa G. Johnston|Pam Sonnenberg|Andrew Copas|Richard Hayes|Richard G. White
Evaluation of Respondent-driven Sampling
respondentdriven sampling novel variant linktracing sampling estimating characteristics hardtoreach groups hiv prevalence sex workers despite use leading health organizations performance method realistic situations still largely unknown evaluated respondentdriven sampling comparing estimates respondentdriven sampling survey total population datatotal population data age tribe religion socioeconomic status sexual activity hiv status available population 2402 male household heads open cohort rural uganda respondentdriven sampling rds survey carried population using current methods sampling rds sample statistical inference rds estimates analyses carried full rds sample repeated first 250 recruits small samplewe recruited 927 household heads full small rds samples largely representative total population samples underrepresented men younger higher socioeconomic status unknown sexual activity hiv status respondentdriven sampling statistical inference methods failed reduce biases 3137 depending method sample size rds estimates closer true population proportions rds sample proportions 5074 respondentdriven sampling bootstrap 95 confidence intervals included population proportionrespondentdriven sampling produced generally representative sample wellconnected nonhidden population however current respondentdriven sampling inference methods failed reduce bias occurred whether data required remove bias measure precision collected respondentdriven sampling survey unresolved respondentdriven sampling regarded potentially superior form convenience sampling method caution required interpreting findings based sampling method