JSM 2004 - Toronto

Abstract #301386

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: 385
Type: Contributed
Date/Time: Wednesday, August 11, 2004 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #301386
Title: Modeling Continuous Bivariate Longitudinal Data
Author(s): Robert E. Weiss*+
Companies: University of California, Los Angeles
Address: School of Public Health, Los Angeles , CA, 90095-1772,
Keywords: random effects ; multivariate ; biostatistics ; correlation
Abstract:

Bivariate longitudinal data occurs when we analyze the interrelationships of two response variables both assessed longitudinally on the same subjects. A common issue when analyzing the two variables is whether and how the two variables are correlated. At the big-picture level, we can ask whether the two variables are correlated or not and is the relationship positive or not. At the detail level, we can ask exactly how the variables are correlated. I review several basic models that can be fit with current software, beginning with the bivariate random intercept model where both residual errors are correlated and the random intercepts are correlated. This model has three important nested submodels and can be expanded to a model where one or both variables has a random slope. Time permitting, I consider additional models: the unstructured covariance model, the product correlation model and factor analytic models.

  • 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