Abstract #302070

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JSM 2003 Abstract #302070
Activity Number: 178
Type: Contributed
Date/Time: Monday, August 4, 2003 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #302070
Title: Analysis of Panel Count Data with Dependent Observation Times
Author(s): Chiung-Yu Huang*+ and Mei-Cheng Wang
Companies: University of Minnesota and Johns Hopkins University
Address: 420 Delaware St. SE, A460 Mayo Bldg., Minneapolis, MN, 55455,
Keywords: panel count data ; dependent observations ; recurrent events ; informative censoring
Abstract:

In many longitudinal studies the observations on recurrent events of study subjects are taken at several distinct time points, and, instead of recording the exact event times, only the number of events that have occurred before each observation time point is known. Data of this type are commonly referred to as panel count data. We assume a multiplicative intensity model, where the form of the baseline intensity function is left unspecified and a subject-specific latent variable acts multiplicatively in the intensity function. The proposed model allows the recurrent event process, observation times, and censoring times to be correlated through their connections with the latent variable; furthermore, the distribution of the latent variable is not parameterized. An estimation procedure for the baseline cumulative intensity function and regression parameters is proposed based on the conditional likelihood function of event counts. Comparisons of the proposed estimator and the maximal likelihood estimator in terms of their bias and efficiency under various degrees of association between the recurrent event process and the observation times will be presented.

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