JSM 2005 Online Program

Abstract #303717

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.

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Activity Number:	312
Type:	Topic Contributed
Date/Time:	Tuesday, August 9, 2005 : 2:00 PM to 3:50 PM
Sponsor:	Section on Bayesian Statistical Science
Abstract - #303717
Title:	Outlier Detection in Spatially Correlated Longitudinal Data with Application to Glaucoma Progression Identification
Author(s):	Luohua Jiang*+ and Gang Li and Robert Weiss
Companies:	University of California, Los Angeles and University of California, Los Angeles and University of California, Los Angeles
Address:	3172 Barrington Ave, Los Angeles, CA, 90066, United States
Keywords:	Hierarchical model ; Bayesian analysis ; doubly spatial model
Abstract:	Reliable detection of glaucomatous deterioration remains one of the most difficult problems facing clinicians in glaucoma management. The difficulty is due to the complex structure of visual field data and the high level of noise in visual field measurements. A single visual field measurement typically consists of visual sensitivity values of 52 locations in an eye. In order to monitor the progression of glaucoma, visual field measurements are acquired periodically for glaucoma patients, yielding spatially correlated longitudinal data. In this work, we develop a Bayesian hierarchical model for visual field data of stable glaucomatous eyes. Different types of outlier statistics representing progressive glaucoma eyes are then defined and used to identify progressive glaucoma eyes.

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