Journal
STATISTICS IN MEDICINE
Volume 35, Issue 20, Pages 3595-3612Publisher
WILEY
DOI: 10.1002/sim.6949
Keywords
CART; censored data; loss estimation; inverse probability of censoring weighted estimation; regression trees; semiparametric estimation
Categories
Funding
- National Institutes of Health [R01CA163687]
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Estimating a patient's mortality risk is important in making treatment decisions. Survival trees are a useful tool and employ recursive partitioning to separate patients into different risk groups. Existing loss based' recursive partitioning procedures that would be used in the absence of censoring have previously been extended to the setting of right censored outcomes using inverse probability censoring weighted estimators of loss functions. In this paper, we propose new doubly robust' extensions of these loss estimators motivated by semiparametric efficiency theory for missing data that better utilize available data. Simulations and a data analysis demonstrate strong performance of the doubly robust survival trees compared with previously used methods. Copyright (c) 2016 John Wiley & Sons, Ltd.
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