A survival tree based on stabilized score tests for high-dimensional covariates

A survival tree can classify subjects into different survival prognostic groups. However, when data contains high-dimensional covariates, the two popular classification trees exhibit fatal drawbacks. The logrank tree is unstable and tends to have false nodes; the conditional inference tree is diffic...

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Bibliographic Details
Published in:	Journal of applied statistics Vol. 50; no. 2; pp. 264 - 290
Main Authors:	Emura, Takeshi, Hsu, Wei-Chern, Chou, Wen-Chi
Format:	Journal Article
Language:	English
Published:	England Taylor & Francis 25.01.2023 Taylor & Francis Ltd
Subjects:	Algorithms CART censoring classification tree Data analysis gene expression logrank test Lung cancer Nodes prognostic prediction Statistical methods Survival prognostic prediction classification tree censoring logrank test gene expression CART
ISSN:	0266-4763, 1360-0532
Online Access:	Get full text
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