Abstract #300091

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JSM 2003 Abstract #300091
Activity Number: 192
Type: Invited
Date/Time: Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor: IMS
Abstract - #300091
Title: An Asymptotic Theory for the Nonparametric Maximum Likelihood Estimator in the Cox-gene Model
Author(s): I-Shou Chang*+ and Chao A. Hsiung and Mei-Chuan Wang and Chi-Chung Wen
Companies: National Health Research Institutes and National Health Research Institutes Taiwan and Taipei Municipal Teachers College and National Health Research Institutes
Address: 3F, 109, Min-Chuan E. Rd., Section 6, Taipei, 114, Taiwan
Keywords: Asymptotically normal ; Cox-gene model ; Nonparametric maximum likelihood estimate ; Profile Likelihood estimate ; Age of onset
Abstract:

The Cox model with the major gene effects for age of onset was introduced and studied by Li, et al. (1998), and Li and Thompson (1997). This talk concerns the nonparametric maximum likelihood estimation of the major gene effects and the regression coefficient in this model. We indicate conditions under which the parameters are identifiable, and the nonparametric maximum likelihood estimate is asymptotically consistent and asymptotically normal. We also apply the theory of observed profile information to get a consistent estimate of the asymptotic variance. Our work provides an alternative approach to the numerical methods in this model, besides providing theoretical support for Li, et al. Simulation studies illustating these methods will also be presented.

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