Competing risk data appear widely in modern biomedical research. Cause-specific hazard models are often used to deal with competing risk data in the past two decades. There is no current study on the kernel likelihood method for the cause-specific hazard model with time-varying coefficients. We propose to use the local partial log-likelihood approach for nonparametric time-varying coefficient estimation. Simulation studies demonstrate that our proposed nonparametric kernel estimator has a good performance under assumed finite sample settings. Finally, we apply the proposed method to analyze a diabetes dialysis study with competing death causes.

翻译：在现代生物医学研究中,相互竞争的风险数据十分广泛。过去二十年来,针对特定原因的危害模型常常被用来处理相互竞争的风险数据。目前没有关于特定原因的危险模型内核可能性方法以及时间分配系数的研究。我们提议使用局部对数对数值的偏差法来估算非参数时间分配系数。模拟研究表明,我们提议的非对数内核估测仪在假定的有限抽样环境中表现良好。最后,我们采用拟议方法分析糖尿病透析研究与相竞争的死亡原因。