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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Parametric randomization-based methods for correcting for treatment changes in the assessment of the causal effect of
A Sarah Walker1, Ian R White, Abdel G Babiker
1MRC Clinical Trials Unit, HIV Division, 222 Euston Road, London NW1 2DA, U.K. asw@cstu.mrc.ac.uk
Abstract:
We develop parametric maximum likelihood methods to adjust for treatment changes during follow-up in order to assess the causal effect of treatment in clinical trials with time-to-event outcomes. The accelerated failure time model of Robins and Tsiatis relates each observed event time to the underlying event time that would have been observed if the control treatment had been given throughout the trial. We introduce a bivariate parametric frailty model for time to treatment change and time to trial endpoint. Estimating equations which respect the randomization are constructed and compared to maximum likelihood methods in a simulation study. The Concorde trial of immediate versus deferred zidovudine in HIV infection is used as a motivating example and illustration of the methods.
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