[HTML][HTML] Nonparametric testing for multiple survival functions with non-inferiority margins

HW Chang, IW McKeague - Annals of statistics, 2019 - ncbi.nlm.nih.gov
Annals of statistics, 2019ncbi.nlm.nih.gov
New nonparametric tests for the ordering of multiple survival functions are developed with
the possibility of right censorship taken into account. The motivation comes from non-
inferiority trials with multiple treatments. The proposed tests are based on nonparametric
likelihood ratio statistics, which are known to provide more powerful tests than Wald-type
procedures, but in this setting have only been studied for pairs of survival functions or in the
absence of censoring. We introduce a novel type of pool adjacent violator algorithm that …
Abstract
New nonparametric tests for the ordering of multiple survival functions are developed with the possibility of right censorship taken into account. The motivation comes from non-inferiority trials with multiple treatments. The proposed tests are based on nonparametric likelihood ratio statistics, which are known to provide more powerful tests than Wald-type procedures, but in this setting have only been studied for pairs of survival functions or in the absence of censoring. We introduce a novel type of pool adjacent violator algorithm that leads to a complete solution of the problem. The limit distributions can be expressed as weighted sums of squares involving projections of certain Gaussian processes onto the given ordered alternative. A simulation study shows that the new procedures have superior power to a competing combined-pairwise Cox model approach. We illustrate the proposed methods using data from a three-arm non-inferiority trial.
ncbi.nlm.nih.gov
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