JSM 2004 - Toronto

Abstract #301662

This is the preliminary program for the 2004 Joint Statistical Meetings in Toronto, Canada. 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, 2004); 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.

Back to main JSM 2004 Program page
Activity Number: 263
Type: Topic Contributed
Date/Time: Tuesday, August 10, 2004 : 2:00 PM to 3:50 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #301662
Title: Bayesian Hierarchical Analysis of Health Services Outcomes Data
Author(s): Benjamin N. Bekele*+ and Linda Elting and Catherine Cooksley
Companies: University of Texas M. D. Anderson Cancer Center and University of Texas M. D. Anderson Cancer Center and University of Texas M. D. Anderson Cancer Center
Address: 1515 Holcombe Blvd.-447, Houston, TX, 77030,
Keywords:
Abstract:

In many health services research studies, observations are correlated, resulting in dependence among outcomes (e.g., subjects nested within hospitals or measurements nested within patients). We will discuss Bayesian approaches that can handle three levels in a hierarchy (i.e., patients nested within surgeons nested within hospitals). Within this Bayesian modeling context, we will discuss methods that can be used to accommodate "imperfect nesting" (i.e., some surgeons practice at more than one hospital). We will give two examples where we fit Bayesian hierarchical regression models (binary outcomes and survival outcomes) from data obtained through public-use databases. We show how to fit such models using WinBugs 1.4 and how to use the new capabilities in WinBugs (e.g., calling WinBugs from S-plus) to more automate the analysis process. (In the past, running univariate models could be very time-consuming).

  • 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 2004 program

JSM 2004 For information, contact jsm@amstat.org or phone (888) 231-3473. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2004