Accelerated Intensity Frailty Model for Recurrent Events Data

作者：Liu Bo^*; Lu Wenbin; Zhang Jiajia

来源：Biometrics, 2014, 70(3): 579-587.

DOI：10.1111/biom.12163

• Accelerated intensity frailty model
• EM algorithm
• Kernel smoothing
• Nonparametric maximum likelihood estimation
• Recurrent events data

In this article we propose an accelerated intensity frailty (AIF) model for recurrent events data and derive a test for the variance of frailty. In addition, we develop a kernel-smoothing-based EM algorithm for estimating regression coefficients and the baseline intensity function. The variance of the resulting estimator for regression parameters is obtained by a numerical differentiation method. Simulation studies are conducted to evaluate the finite sample performance of the proposed estimator under practical settings and demonstrate the efficiency gain over the Gehan rank estimator based on the AFT model for counting process (Lin et al., 1998). Our method is further illustrated with an application to a bladder tumor recurrence data.

• 出版日期2014-9