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Biostatistics 2005 6(1):77-91; doi:10.1093/biostatistics/kxh019
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Biostatistics Vol. 6 No. 1 © Oxford University Press 2005; all rights reserved.

Sensitivity analysis for informative censoring in parametric survival models

Fotios Siannis*

MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 2SR, UK fotios.siannis{at}mrc-bsu.cam.ac.uk

John Copas

Department of Statistics, University of Warwick, Coventry CV4 7AL, UK

Guobing Lu

MRC HSRC, Department of Social Medicine, University of Bristol, Canynge Hall, Whiteladies Road, Bristol BS8 2PR, UK

* To whom correspondence should be addressed.

Most statistical methods for censored survival data assume there is no dependence between the lifetime and censoring mechanisms, an assumption which is often doubtful in practice. In this paper we study a parametric model which allows for dependence in terms of a parameter {delta} and a bias function B(t, {theta}). We propose a sensitivity analysis on the estimate of the parameter of interest for small values of {delta}. This parameter measures the dependence between the lifetime and the censoring mechanisms. Its size can be interpreted in terms of a correlation coefficient between the two mechanisms. A medical example suggests that even a small degree of dependence between the failure and censoring processes can have a noticeable effect on the analysis.

Keywords: Sensitivity analysis; informative censoring; proportional hazard models


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