Abstract Details
Activity Number:
|
36
|
Type:
|
Contributed
|
Date/Time:
|
Sunday, August 9, 2015 : 2:00 PM to 3:50 PM
|
Sponsor:
|
Biometrics Section
|
Abstract #316462
|
|
Title:
|
Bayesian Dynamic Survival Model with Covariate-Varying Coefficients and Its Applications to Epidemiologic Research
|
Author(s):
|
Jianghua He*
|
Companies:
|
University of Kansas Medical Center
|
Keywords:
|
Time-varying coefficient ;
survival analysis ;
2-dimensional smoothing ;
Body mass index ;
mortality
|
Abstract:
|
For epidemiologic Research, traditional analysis approaches such as the logistic regression model and the Cox proportional model ignore the potential changing relationship over time. Various time-varying coefficients survival models have been proposed in the literature to overcome such limitations. The Bayesian Dynamic Survival Model approaches the issue from the Bayesian perspective and is more flexible in modeling time-varying coefficients. Sometimes, the time-varying coefficients may also change with ontinuous covariates. A Bayesian dynamic survival model with covariate-varying coefficients is proposed to model flexible associations in both the time and the covariate dimensions. The implementation of such a model can be conducted easily based on a transformation of survival data. This Bayesian dynamic survival model is applied to examine the association of body weight and mortality in a Meta analyses based on multiple cohorts with different characteristics.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2015 program
|
For program information, contact the JSM Registration Department or phone (888) 231-3473.
For Professional Development information, contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
2015 JSM Online Program Home
ASA Meetings Department
732 North Washington Street, Alexandria, VA 22314
(703) 684-1221 • meetings@amstat.org
Copyright © American Statistical Association.