JSM 2005 Online Program

Abstract #303051

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:	123
Type:	Topic Contributed
Date/Time:	Monday, August 8, 2005 : 10:30 AM to 12:20 PM
Sponsor:	Section on Health Policy Statistics
Abstract - #303051
Title:	A Comparison of Estimators of Population Slope under Informative Dropout
Author(s):	Hai (Kevin) Lin*+ and Elizabeth Slate
Companies:	The University of Texas M. D. Anderson Cancer Center and Medical University of South Carolina
Address:	Science Park Research Division, Smithville, TX, 78957, United States
Keywords:	longitudinal study ; population slope estimates ; informative dropout
Abstract:	We address estimation of the population slope of a longitudinal response in the presence of informative dropout. Traditional methods, such as generalized mixed model analyses, do not account for informative dropout and can produce biased estimates of the population slope. We use a simulation study to investigate the performance of four estimators of population slope under dropout of varying degrees of informativeness. The four estimators are the weighted and unweighted least squares methods, the empirical Bayes method (Mori et al.. 1992), and the informative right censoring adjusted estimator (IRCAE). The estimators are evaluated by MSE and bias. Of particular interest is the new comparison of the empirical Bayes estimator to IRCAE, for which our results show empirical Bayes with less bias and less MSE than IRCAE for the differing degrees of informativeness. However, both empirical Bayes and IRCAE estimates are more attractive and competitive than both the weighted and unweighted methods under informative censoring. We apply all four methods to data from two clinical trials.

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