Estimation For the Survival Function of Quality Adjusted Lifetime رسالة ماجستير

Abstract

Recently, quality adjusted life time has received much attention because of its ability to take quality of life into consideration. The quality adjusted lifetime is a new approach to therapy evaluation in clinical trials. In this work we will present the case of censoring, assuming that a subject disappears at specific time, and reports back at any time later. We will deal with this type of censoring using two methods: 'The Mean Value Theorem method and the shifting method.

Also, we will ind another estimator for the survival function, using the Monotonized Zhao-Tiatis estimator and Wang estimator by following Almanssra method(2005). We will study the eficiency of this estimator using simulation study to compare MSE, BIAS for the estimations and the true value of survival function by using R program.