现状数据下带测量误差的半参数加速风险模型的估计

Estimation for Semi-parametric Accelerated Hazard Model with Measurement Error under Current Status Data

基于现状数据提出一种带有测量误差的半参数加速风险回归模型.首先,用I样条近似未知累积基线风险函数,并基于Sieve极大似然估计方法获得模型的参数估计;其次,用模拟外推方法修正协变量的测量误差带来的估计误差;再次,通过数值模拟验证该方法的有效性以及忽略协变量误差对估计的影响;最后将该方法应用到心脑血管病死亡率的研究中获得心脑血管病发死亡的风险函数估计.实验结果表明,该方法有效.

We proposed a semi-parametric accelerated hazard regression model with measurement errors based on the current status data.Firstly,the unknown baseline cumulative hazard function was approximated by using I-spline,and parameter estimates of the model were obtained based on Sieve maximum likelihood estimation method.Secondly,a simulation extrapolation method was used to correct estimation error caused by measurement errors in covariates.Thirdly,the numerical simulations were carried out to verify the effectiveness of the proposed method as well as the impact of ignoring measurement error in covariates.Finally,the proposed method was applied to study cardiovascular and cerebrovascular disease mortality,we obtained estimation of hazard function for cardiovascular and cerebrovascular disease mortality.The experimental results show that the proposed method is effective.