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Abstract:
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The method of generalized pairwise comparisons (GPC) allows comparing two groups of observations based on multiple hierarchically-ordered endpoints, regardless of their number or type. The summary measure, ``net benefit'', quantifies the difference between the probabilities that a random observation from one group is ``better'' than an observation from the opposite group. The method takes into account the correlations between the endpoints. We have performed a simulation study for the case of two endpoints to evaluate the impact of the correlation on the type-I error probability and power of the test based on GPC. The simulations show that the overall power of the hierarchical GPC procedure depends, in a complex manner, on the entire variance-covariance structure of the set of outcomes. The change in power when the secondary endpoint is included in the GPC analysis depends on the correlation between the endpoints. Interestingly, a decrease in power can occur regardless of whether there is any marginal treatment effect on the secondary endpoint. Anticipating correlations between the outcomes might be challenging when designing a trial based on the hierarchical GPC procedure.
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