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Biometrika 2002 89(3):659-668; doi:10.1093/biomet/89.3.659
© 2002 by Biometrika Trust
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Semiparametric analysis of transformation models with censored data

Kani Chen1, Zhezhen Jin2 and Zhiliang Ying3

1 Department of Mathematics, Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong makchen{at}ust.hk 2 Department of Biostatistics, Mailman School of Public Health, Columbia University, 600 West 168th Street, New York, New York 10032, U.S.Azjin{at}biostat.columbia.edu 3 Department of Statistics, Columbia University, 2990 Broadway, New York, New York 10027, U.S.A.zying{at}stat.columbia.edu

A unified estimation procedure is proposed for the analysis of censored data using linear transformation models, which include the proportional hazards model and the proportional odds model as special cases.This procedure is easily implemented numerically and its validity does not rely on the assumption of independence between the covariates and the censoring variable. The estimator is the same as the Cox partial likelihood estimator in the case of the proportional hazards model. Moreover, the asymptotic variance of the proposed estimator has a closed form and its variance estimator is easily obtained by plug-in rules. The method is illustrated by simulation and is applied to the Veterans' Administration lung cancer data.

Key Words: Estimating equation; Linear transformation model; Proportional hazards model; Proportional odds model

Received March 2001. Revised February 2002


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