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Estimating effectiveness in HIV prevention trials with a Bayesian hierarchical compound Poisson frailty model
Author(s) -
Coley Rebecca Yates,
Brown Elizabeth R.
Publication year - 2016
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.6884
Subject(s) - psychological intervention , poisson distribution , bayesian probability , medicine , poisson regression , population , human immunodeficiency virus (hiv) , random effects model , econometrics , statistics , environmental health , mathematics , meta analysis , family medicine , psychiatry
Inconsistent results in recent HIV prevention trials of pre‐exposure prophylactic interventions may be due to heterogeneity in risk among study participants. Intervention effectiveness is most commonly estimated with the Cox model, which compares event times between populations. When heterogeneity is present, this population‐level measure underestimates intervention effectiveness for individuals who are at risk. We propose a likelihood‐based Bayesian hierarchical model that estimates the individual‐level effectiveness of candidate interventions by accounting for heterogeneity in risk with a compound Poisson‐distributed frailty term. This model reflects the mechanisms of HIV risk and allows that some participants are not exposed to HIV and, therefore, have no risk of seroconversion during the study. We assess model performance via simulation and apply the model to data from an HIV prevention trial. Copyright © 2016 John Wiley & Sons, Ltd.