ArticleLifetime data analysis2020
Bootstrap and permutation rank tests for proportional hazards under right censoring.
Article in Lifetime data analysis, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Re-examination of statistical relationships between dietary fats and other risk factors, and cardiovascular disease, based on two crucial datasets.Quantitative biology (Beijing, China) · 2024Article
- Studentized permutation method for comparing two restricted mean survival times with small sample from randomized trials.Statistics in medicine · 2023Article
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Authors and funding
2 authors.
Funding
Abstract
We address the testing problem of proportional hazards in the two-sample survival setting allowing right censoring, i.e., we check whether the famous Cox model is underlying. Although there are many test proposals for this problem, only a few papers suggest how to improve the performance for small sample sizes. In this paper, we do exactly this by carrying out our test as a permutation as well as a wild bootstrap test. The asymptotic properties of our test, namely asymptotic exactness under the null and consistency, can be transferred to both resampling versions. Various simulations for small sample sizes reveal an actual improvement of the empirical size and a reasonable power performance when using the resampling versions. Moreover, the resampling tests perform better than the existing tests of Gill and Schumacher and Grambsch and Therneau . The tests' practical applicability is illustrated by discussing real data examples.
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