American Statistical Association
The mean residual life function is an alternative to the survival function or the hazard function of a survival time in practice. It provides the remaining life expectancy of a subject surviving up to t. In this study, we propose a class of transformed mean residual life models for fitting survival data under right censoring. To estimate the model parameter, we make use of the inverse probability of censoring weighting approach and develop a system of estimating equations. Both asymptotic and finite sample properties of the proposed estimators are established and the approach is applied to two real life data sets collected from a clinical trial. We also considered the efficiency and double robustness of our estimator, and developed a model checking technique for one of the special cases of the transformation models.
|Date:||Wednesday, April 1, 2009|
|Time:||4:00 - 5:00 P.M.|
Memorial Sloan-Kettering Cancer Center
Department of Epidemiology and Biostatistics
307 East 63rd Street
(between First and Second Avenues)
3rd Floor Conference Room
New York, New York
Note: To gain access to the building, please follow the directions by the telephone in the foyer.