This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 416
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section on Nonparametric Statistics
Abstract - #309099
Title: Shrinkage Nonparametric Estimation of Median Survival Time from Censored Data
Author(s): Mohammad Hossein Rahbar*+ and Weiwei Wang and Jing Ning
Companies: The University of Texas Health Science Center at Houston and The University of Texas Health Science Center at Houston and The University of Texas Health Science Center at Houston
Address: 6410 Fannin St., Suite 1100.05, Houston, TX, 77030,
Keywords: Nonparametric analysis ; survival analysis ; shrinkage estimation ; pretest estimation ; censored data ; simulations
Abstract:

We present a basic methodology for estimation in a nonparametric model that may be either under-or over- specified. Specifically, we focus on unrestricted, pretest, and shrinkage estimation of the median survival time from several independent samples of censored data. Assuming the hypothesis of homogeneity is tenable the vector of median survival times is estimated from the combined sample, or by combining the estimates from each sample with some prior non-sample information. We present asymptotic properties of seven nonparametric procedures for the estimation of median survival time: unrestricted (UE), combined (CE), shrinkage combined (SCE), pretest (PTE), shrinkage pretest (SPTE), Stein-type shrinkage (SSE), and positive part shrinkage (PSE). Through simulation studies we compute asymptotic risks using squared error loss. We compare the relative efficiency of these procedures.


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