JSM 2005 Online Program

Abstract #303506

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:	74
Type:	Contributed
Date/Time:	Sunday, August 7, 2005 : 8:00 PM to 9:50 PM
Sponsor:	General Methodology
Abstract - #303506
Title:	Utilizing Propensity Scores To Test Treatment Effects in Survival Data
Author(s):	Jingxia Liu*+ and Meijie Zhang
Companies:	Medical College of Wisconsin and Medical College of Wisconsin
Address:	8701 Watertown Plank Rd, Milwaukee, WI, 53213, United States
Keywords:	Propensity Score ; Treatment Effects ; Survival data
Abstract:	Randomized clinical trials often are considered the gold standard in examining the treatment outcome. Due to various reasons, it is not always feasible to carry out a randomized experiment. Thus, we need to estimate treatment effects from observational cohorts. However, patients receiving one treatment are not guaranteed to be prognostically comparable to those receiving another treatment, so the observed difference in outcomes may come from the differences in covariates in the two groups rather than the effect of the treatment. In this paper, we are interested in evaluating the treatment effect using data from registration databases, especially time-to-event data. The specific goal is to study a treatment effect of time-to-event data using \ps\ in observational studies. The large sample properties of the proposed new methods are studied and exemplified using a real dataset. The performance of various procedures for fixed sample sizes is investigated through simulation studies.

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