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arXiv · 2006.14316

Inferring median survival differences in general factorial designs via permutation tests

Marc Ditzhaus·Dennis Dobler·Markus Pauly
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Abstract

Factorial survival designs with right-censored observations are commonly inferred by Cox regression and explained by means of hazard ratios. However, in case of non-proportional hazards, their interpretation can become cumbersome; especially for clinicians. We therefore offer an alternative: median survival times are used to estimate treatment and interaction effects and null hypotheses are formulated in contrasts of their population versions. Permutation-based tests and confidence regions are proposed and shown to be asymptotically valid. Their type-1 error control and power behavior are investigated in extensive simulations, showing the new methods' wide applicability. The latter is complemented by an illustrative data analysis.

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Marc Ditzhaus, Dennis Dobler, Markus Pauly. 2020-06-25. Inferring median survival differences in general factorial designs via permutation tests. https://arxiv.org/abs/2006.14316

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