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We describe methods for designing non-inferiority trials with recurrent event responses arising from mixed-Poisson models. Sample size formulae are derived for trials in which treatment effects are expressed as relative rates and as absolute differences in cumulative mean functions at a particular time. Simulation studies are conducted to provide empirical validation of the frequency properties of the design and testing procedures under the null and alternative hypotheses using both mixed-Poisson models and robust marginal methods. The robustness of the design to mis-specification of the random effect distribution is also studied empirically. Sample size requirements based on the proposed method are contrasted with those from a design based on the time to the first event for a motivating study of patients with bone metastases at risk of skeletal complications. When the between-patient heterogeneity in the event rate is small, there may be a considerable reduction in sample size with recurrent event outcomes.
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Cook et al. (2007) studied this question.
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