JSM 2005 - Toronto

Abstract #304530

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 447
Type: Contributed
Date/Time: Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor: General Methodology
Abstract - #304530
Title: Inference for the Bivariate Positive Stable Frailty Models
Author(s): Madhuja Mallick*+ and Nalini Ravishanker
Companies: Merck Research Laboratories and University of Connecticut
Address: RY34A316, Rahway, NJ, 07065, United States
Keywords: bivariate stable ; piecewise exponential
Abstract:

The univariate shared frailty models have several drawbacks. In many applications, the situation arises where the subjects in the same group possess different frailty random components rather than sharing similar frailty components within the group. The notion of multivariate frailty enables us to overcome the difficulties of univariate shared frailty models. This presentation proposes bivariate positive stable frailty model to incorporate more heterogeneity than the shared positive stable frailty model. The estimation procedure for bivariate positive stable density is not easy due to lack of closed form of the bivariate positive stable density function. The inference for the bivariate positive stable frailty model for multivariate survival data is described using a flexible semiparametric baseline hazard formulation. For the simplicity of the estimation procedure, the basis of a simplified assumption--- such as likelihood function---is derived by replacing a high-dimensional integration by Monte Carlo simulation, and Markov Chain Monte Carlo algorithms then enables estimation and model checking in the Bayesian framework.

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