JSM 2005 Online Program

Abstract #303237

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

To View the Program:
You may choose to view all activities of the program or just parts of it at any one time. All activities are arranged by date and time.

The views expressed here are those of the individual authors
and not necessarily those of the ASA or its board, officers, or staff.

The Program has labeled the meeting rooms with "letters" preceding the name of the room, designating in which facility the room is located:

Minneapolis Convention Center = “MCC” Hilton Minneapolis Hotel = “H” Hyatt Regency Minneapolis = “HY”

Back to main JSM 2005 Program page

Legend:

= Applied Session,

= Theme Session,

= Presenter

Activity Number:	450
Type:	Contributed
Date/Time:	Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor:	Section on Nonparametric Statistics
Abstract - #303237
Title:	Shrinkage Nonparametric Estimation of Mean Survival Time from Censored Data
Author(s):	Mohammad Rahbar*+ and Alla Sikorskii and S. Ejaz Ahmed and Sangchoon Jeon and Joseph C. Gardiner
Companies:	Michigan State University and Michigan State University and University of Windsor and Michigan State University and Michigan State University
Address:	Room 100 Conrad Hall, East Lansing, MI, 48824, United States
Keywords:	Nonparametric ; survival analysis ; shrinkage estimation ; pretest estimation ; censored data ; simulations
Abstract:	We develop a basic methodology for estimation in a nonparametric model that may be under- or over-specified. Specifically, we focus on unrestricted, pretest, and shrinkage estimation of the mean survival time from several independent samples of censored data. Assuming the hypothesis of homogeneity is tenable, the vector of mean survival times is estimated from the combined sample or from combining the estimates from each sample and some prior nonsample information. We present asymptotic properties of seven nonparametric procedures for the estimation of mean 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 efficiency of these procedures relative to CE using ratio of the asymptotic risks. Our results indicate performance of these estimation procedures depends on the strength of homogeneity. When homogeneity holds, the CE is the most efficient estimator.

The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.

Back to the full JSM 2005 program