 Tests for comparing estimated survival functionsC. Chauvel and J. O'Quigley Biometrika, 2014, vol. 101, issue 3, 535-552 Abstract: We describe a class of statistical tests for the comparison of two or more survival curves, typically estimated using the Kaplan–Meier method. The class is based on the construction of O’Quigley (2003), and some special cases are of particular interest. Underlying the inferential development are the arguments of Efron & Hinkley (1978), leading to a theoretical sampling model that is in some sense closer to the observed data. The log-rank and weighted log-rank tests arise as special members of the class. In practice the log-rank test will often be a suboptimal, even poor, test due to the presence of non-proportional hazards. The proposed test maintains good power and, in all the cases considered, has greater power than the log-rank test under non-proportional hazards. The power will depend on the alternatives being considered, and under reasonable assumptions on the alternatives, we conclude that the proposed test is more powerful than the log-rank test. Simulations support these conclusions. An example is given as an illustration. Date: 2014 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:oup:biomet:v:101:y:2014:i:3:p:535-552. Ordering information: This journal article can be ordered from Access Statistics for this article Biometrika is currently edited by Paul Fearnhead More articles in Biometrika from Biometrika Trust Oxford University Press, Great Clarendon Street, Oxford OX2 6DP, UK. |
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