Proportional Mean Residual Life Model with Censored Survival Data under Case-cohort Design

TL;DR

This paper develops a new method for estimating the mean residual life in survival analysis with censored data under a case-cohort design, providing consistent and efficient estimators validated by simulations and real data application.

Contribution

It introduces weighted estimating equations for simultaneous estimation of regression parameters and baseline mean residual life in case-cohort survival data.

Findings

Estimators are consistent and asymptotically normal.

Simulation studies confirm good performance of the estimators.

Application to real data demonstrates practical utility.

Abstract

Proportional mean residual life model is studied for analysing survival data from the case-cohort design. To simultaneously estimate the regression parameters and the baseline mean residual life function, weighted estimating equations based on an inverse selection probability are proposed. The resulting regression coefficients estimates are shown to be consistent and asymptotic normal with easily estimated variance-covariance. Simulation studies show that the proposed estimators perform very well. An application to a real dataset from the South Welsh nickel refiners study is also given to illustrate the methodology.