Implications of Model Misspecification in Robust Tests for Recurrent Events |
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Authors: | J Boher R J Cook |
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Institution: | (1) Department of Statistics and Actuarial Science, University of Waterloo, 200 University Avenue West, Waterloo, Ontario, Canada, N2L 3G1 |
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Abstract: | Chronic disease processes often feature transient recurrent adverse clinical events. Treatment comparisons in clinical trials
of such disorders must be based on valid and efficient methods of analysis. We discuss robust strategies for testing treatment
effects with recurrent events using methods based on marginal rate functions, partially conditional rate functions, and methods
based on marginal failure time models. While all three approaches lead to valid tests of the null hypothesis when robust variance
estimates are used, they differ in power. Moreover, some approaches lead to estimators of treatment effect which are more
easily interpreted than others. To investigate this, we derive the limiting value of estimators of treatment effect from marginal
failure time models and illustrate their dependence on features of the underlying point process, as well as the censoring
mechanism. Through simulation, we show that methods based on marginal failure time distributions are shown to be sensitive
to treatment effects delaying the occurrence of the very first recurrences. Methods based on marginal or partially conditional
rate functions perform well in situations where treatment effects persist or in settings where the aim is to summarizee long-term
data on efficacy. |
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Keywords: | Bias Marginal Model misspecification Power Partially conditional Recurrent events |
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