JSM 2004 - Toronto

Abstract #300100

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Activity Number: 169
Type: Invited
Date/Time: Tuesday, August 10, 2004 : 8:30 AM to 10:20 AM
Sponsor: WNAR
Abstract - #300100
Title: Analyzing Longitudinal Data with Informative Censoring: Repeated Measurements vs. Recurrent-event Data
Author(s): Mei-Cheng Wang*+
Companies: Johns Hopkins University
Address: Dept. of Biostatistics, School of Public Health, Baltimore, MD, 21205,
Keywords: informative censoring ; repeated measurements ; recurrent events
Abstract:

Repeated measurements and recurrent events can both be classified as longitudinal data since they are commonly observed in longitudinal follow-up studies. In general, statistical methods developed for data from one of the two categories are not automatically applicable to data from the other category because of differences in the data characteristics. This talk presents an informative censoring model for data of each category, and shows that under the specified models these two kinds of data share some common features. These features give us advantages to develop statistical methods which are applicable to both kinds of data. The "shape" and "size" parameters are introduced to characterize, model, and analyze repeated measurements and recurrent event data.

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Revised March 2004