Sensitivity analysis for informative censoring in parametric survival models.
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.
Siannis
Fotios
F
MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 2SR, UK. fotios.siannis@mrc-bsu.cam.ac.uk
Copas
John
J
Lu
Guobing
G
D003627:Data Interpretation, Statistical; D006801:Humans; D009101:Multiple Myeloma / Q000401:mortality; D016016:Proportional Hazards Models; D012680:Sensitivity and Specificity; D016019:Survival Analysis