Inferring median survival differences in general factorial designs via permutation tests
Methodology
2020-06-26 v1
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.
Keywords
Cite
@article{arxiv.2006.14316,
title = {Inferring median survival differences in general factorial designs via permutation tests},
author = {Marc Ditzhaus and Dennis Dobler and Markus Pauly},
journal= {arXiv preprint arXiv:2006.14316},
year = {2020}
}