© 1995 by Biometrika Trust
Articles |
Analysis of transformation models with censored data
Department of Biomathematics, M. D. Anderson Cancer Center, University of Texas 1515 Holcombe Boulevard, Box 237, Houston, Texas 77030, U.S.A.
Department of Biostatistics, Harvard University 677 Huntington Avenue, Boston, Massachusetts 02115, U.S.A.
Department of Statistics, Rutgers University New Brunswick, New Jersey 08903, U.S.A.
Received for publication 1 December 1994.
Revision received 1 May 1995.
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Abstract |
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In this paper we consider a class of semi-parametric transformation models, under which an unknown transformation of the survival time is linearly related to the covariates with various completely specified error distributions. This class of regression models includes the proportional hazards and proportional odds models. Inference procedures derived from a class of generalised estimating equations are proposed to examine the covariate effects with censored observations. Numerical studies are conducted to investigate the properties of our proposals for practical sample sizes. These transformation models, coupled with the new simple inference procedures, provide many useful alternatives to the Cox regression model in survival analysis.
Key Words: Generalised estimating equation • Martingale • Proportional hazards model • Proportional odds model • U-statistic
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