Semiparametric Box–Cox power transformation models for censored survival observations

• Published in: Biometrika Vol. 92; no. 3; pp. 619 - 632
• Main Authors: Tian, Lu, Cai, Tianxi, Wei, L. J
• Format: Journal Article
• Language: English
• Published: Oxford University Press for Biometrika Trust 01.09.2005
• Series: Biometrika
• ISSN: 0006-3444; 1464-3510
• DOI: 10.1093/biomet/92.3.619

The accelerated failure time model specifies that the logarithm of the failure time is linearly related to the covariate vector without assuming a parametric error distribution. In this paper, we consider the semiparametric Box--Cox transformation model, which includes the above regression model as a special case, to analyse possibly censored failure time observations. Inference procedures for the transformation and regression parameters are proposed via a resampling technique. Prediction of the survival function of future subjects with a specific covariate vector is also provided via pointwise and simultaneous interval estimates. All the proposals are illustrated with datasets from two clinical studies. Copyright 2005, Oxford University Press.