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Activity Number: 269
Type: Topic Contributed
Date/Time: Tuesday, August 8, 2006 : 10:30 AM to 12:20 PM
Sponsor: Section on Bayesian Statistical Science
Abstract - #307368
Title: A Hierarchical Bayesian Analysis of Longitudinal Frequency Data Using Piecewise Linear Regression
Author(s): John Kern*+ and Nicholas Bernini and Sujit Ghosh
Companies: Duquesne University and Duquesne University and North Carolina State University
Address: 600 Forbes Ave., Pittsburgh, PA, 15282,
Keywords: Poisson regression ; knot locations ; MCMC
Abstract:

Piecewise linear Poisson regression is used to model, for a specific individual, the mean frequency of a particular event as a function of time. Parameters of this model include the knot locations of the piecewise linear function and are estimated using MCMC sampling techniques. The hierarchical component of the model allows for the estimation of treatment group profiles and hence for direct group comparison. We apply this model to frequency data collected from breast cancer survivors receiving menopausal symptom relief treatment.

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