@article {22510, title = {
Sensitivity analysis for informative censoring in
parametric survival models
}, journal = {Biostatistics}, volume = {6}, year = {2005}, pages = {77-91}, abstract = {

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 δ and a bias function B(t, θ).\ We propose a sensitivity analysis on the estimate of the parameter of interest for small values of δ. 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.

}, url = {https://watermark.silverchair.com/kxh019.pdf?token=AQECAHi208BE49Ooan9kkhW_Ercy7Dm3ZL_9Cf3qfKAc485ysgAAArMwggKvBgkqhkiG9w0BBwagggKgMIICnAIBADCCApUGCSqGSIb3DQEHATAeBglghkgBZQMEAS4wEQQMnE0SOBHj3FfrS3A6AgEQgIICZk0sor7BOR0_EoK63cKBPvc8gRFAES_a-jyGEC_CpBAYJpqS}, author = {Fotios Siannis and JOHN COPAS and GUOBING LU} }