Statistics in medicine
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First generation HIV vaccines are not likely to provide complete protection from HIV-1 infection. Therefore, it is important to assess a vaccine's effect on disease progression and infectiousness of infected vaccinees in an efficacy trial; however, direct assessment of such vaccine effects is not feasible within current trial designs. Viral load in HIV-infected individuals correlates with infectiousness and disease progression in a natural history setting, and thus is a reasonable candidate for a surrogate outcome in vaccine efficacy trials. ⋯ Thus, the usual statistical tests for no difference between groups do not test the biologically and clinically relevant hypothesis. We propose a model for the possible selective effects of a vaccine and develop several test statistics for assessing a direct effect of the vaccine on viral load given this selection model. Finite sample properties of these tests are evaluated using computer simulations.