An Asymptotically Optimal Adaptive Selection Procedure in the Proportional Hazards Model with Conditionally Independent Censoring

Abstract

Assume k independent populations are given which are distributed according toTaking samples of size n the population with the smallest J-value is to be selected. Using the framework of Le Cam's decision theory (Le Cam, 1986;Strasser, 1985) under mild regularity assumptions, an asymptotically optimal selection procedure is derived for the sequence of localized models. In the proportional hazards model with conditionally independent censoring, an asymptotically optimal adaptive selection procedure is constructed by substituting the unknown nuisance parameter by a kernel estimator.

Frailty Models in Survival Analysis

“…Their method involves further follow-up of a subpopulation of lost-to-follow-up censored subjects. Asymptotic results in a specific situation are obtained by Wienke (1998). All these methods consider uncorrelated subjects only.…”