Goodness-of-fit test for the parametric proportional hazard regression model with interval-censored data
Goodness-of-fit test for the parametric proportional hazard regression model with interval-censored data
复制标题
区间删失数据参数比例风险回归模型的拟合优度检验
DOI：
10.1080/24709360.2018.1529347
复制
发表时间：
2018
影响因子：
--
通讯作者：
Hattori Satoshi
中科院分区：
文献类型：
--
作者：
Sakurai Rieko;Hattori Satoshi
间隔审查数据在医学研究中很常见。全参数模型为使用区间截除观测值估计生存函数提供了简单有效的推断。基于参数回归模型的推理需要对概率密度函数进行完整的说明，因此，正确地指定模型是至关重要的，而回归诊断是非常重要的一步。然而，用于区间截除数据的回归诊断方法尚未完全开发。在这里，我们开发了一种基于累积鞅残差的模型检查程序。我们采用残差的条件期望进行诊断，因为显示准确故障时间的数据无法用于区间审查分析，并开发了基于重采样的形式化最高类型测试和图形模型检查技术。仿真研究表明，在有限样本中检测协变量的错误函数形式时，所提出的方法具有优异的性能。此外，我们将此方法用于分析在日本获得的体检数据。
Interval-censored data are common in medical research. Fully parametric models provide simple and efficient inference for the estimation of survival functions using interval-censored observations. Inference based on a parametric regression model requires the complete specification of the probability density function, and therefore, correctly specifying the model is crucial, while the regression diagnostic is a very important step. However, regression diagnostic methods for use with the interval-censored data have not been completely developed. Here, we developed a model-checking procedure based on the cumulative martingale residuals for the interval-censored observations. We employed the conditional expectation of residuals for the diagnostics, because the data showing the exact failure time cannot be obtained for the interval-censoring analyses, and developed the formal resamplingbased supremum-type test and graphical model-checking techniques. A simulation study demonstrated an excellent performance of the proposed method during the detection of misspecified functional form of covariates in the finite sample. Furthermore, we used this method for the analysis of the medical checkup data obtained in Japan.