Accelerated Hazards Model Based on Parametric Families Generalized with Bernstein Polynomials

作者：Chen Yuhui^*; Hanson Timothy; Zhang Jiajia

来源：Biometrics, 2014, 70(1): 192-201.

DOI：10.1111/biom.12104

• Accelerated hazards model
• Bayesian nonparametric prior
• Survival analysis
• Time dependent covariate

A transformed Bernstein polynomial that is centered at standard parametric families, such as Weibull or log-logistic, is proposed for use in the accelerated hazards model. This class provides a convenient way towards creating a Bayesian nonparametric prior for smooth densities, blending the merits of parametric and nonparametric methods, that is amenable to standard estimation approaches. For example optimization methods in SAS or R can yield the posterior mode and asymptotic covariance matrix. This novel nonparametric prior is employed in the accelerated hazards model, which is further generalized to time-dependent covariates. The proposed approach fares considerably better than previous approaches in simulations; data on the effectiveness of biodegradable carmustine polymers on recurrent brain malignant gliomas is investigated.

• 出版日期2014-3