论文标题
协变量中具有测量误差的半参数转换模型：仪器变量方法
Semiparametric transformation Model with measurement error in Covariates: An Instrumental variable approach
论文作者
论文摘要
线性转化模型提供了一个通用框架，用于分析使用协变量审查的生存数据。比例危害和比例赔率模型是线性转化模型的特殊情况。在生物医学研究中，生存数据中可能发生具有测量误差的协变量。在这项工作中，我们提出了一种方法，以获取线性转换模型中回归系数的估计值，当协变量遇到测量误差时。在提出的方法中，我们假设可以使用仪器变量。我们开发基于计数过程的估计方程，以查找回归系数的估计值。 我们使用回归估计器的martingale表示证明了估计量的较大样本特性。通过广泛的蒙特卡洛模拟研究评估估计量的有限样本性能。最后，我们使用AIDS临床试验（ACTG 175）数据说明了提出的方法。
Linear transformation model provides a general framework for analyzing censored survival data with covariates. The proportional hazards and proportional odds models are special cases of the linear transformation model. In biomedical studies, covariates with measurement error may occur in survival data. In this work, we propose a method to obtain estimators of the regression coefficients in the linear transformation model when the covariates are subject to measurement error. In the proposed method, we assume that instrumental variables are available. We develop counting process based estimating equations for finding the estimators of regression coefficients. We prove the large sample properties of the estimators using the martingale representation of the regression estimators. The finite sample performance of the estimators are evaluated through an extensive Monte Carlo simulation study. Finally, we illustrate the proposed method using an AIDS clinical trial (ACTG 175) data.
