Abstract #300112

This is the preliminary program for the 2003 Joint Statistical Meetings in San Francisco, California. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 2-5, 2003); 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 2003 Program page
JSM 2003 Abstract #300112
Activity Number: 454
Type: Contributed
Date/Time: Thursday, August 7, 2003 : 8:30 AM to 10:20 AM
Sponsor: Biopharmaceutical Section
Abstract - #300112
Title: A Statistical Methodology for Analyzing Longitudinal Data
Author(s): Shenghai Zhang*+ and Mary E. Thompson
Companies: University of Waterloo and University of Waterloo
Address: 225B Cedarbrae Ave., Waterloo, ON, N2L 4S6, Canada
Keywords: clustered data ; one-step estimator ; GEE
Abstract:

The generalized estimating equations (GEE) methodology is considered the most popular approach for estimating both the regression parameters and correlations in marginal models for repeated responses. However, it may be difficult to find the roots of the estimating equations. The estimating equation must behave well throughout the parameter set for the roots to be consistent. Difficulties arise, for example, if there exists a second root which is close to the boundary of the parameter set. Since we need an estimator for the nuisance parameter in the correlation structure, the conventional GEE method can lead to a breakdown of estimation for the regression parameters. A one-step method may overcome these problems by building on and improving preliminary estimators. We will provide a one-step GEE estimator which extends the method considered by Lipsitz, et al., for analyzing repeated binary responses, and give a theoretical justification. Properties such as bias of the estimator, efficiency and the role

  • 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 2003 program

JSM 2003 For information, contact meetings@amstat.org or phone (703) 684-1221. If you have questions about the Continuing Education program, please contact the Education Department.
Revised March 2003