Reeves G K, Cox D R, Darby S C, Whitley E
Imperial Cancer Research Fund Cancer Epidemiology Unit, University of Oxford, U.K.
Stat Med. 1998 Oct 15;17(19):2157-77. doi: 10.1002/(sici)1097-0258(19981015)17:19<2157::aid-sim916>3.0.co;2-f.
A simple form of measurement error model for explanatory variables is studied incorporating classical and Berkson cases as particular forms, and allowing for either additive or multiplicative errors. The work is motivated by epidemiological problems, and therefore consideration is given not only to continuous response variables but also to logistic regression models. The possibility that different individuals in a study have errors of different types is also considered. The relatively simple estimation procedures proposed for use with cohort data and case-control data are checked by simulation, under the assumption of various error structures. The results show that even in situations where conventional analysis yields slope estimates that are on average attenuated by a factor of approximately 50 per cent, estimates obtained using the proposed amended likelihood functions are within 5 per cent of their true values. The work was carried out to provide a method for the analysis of lung cancer risk following residential radon exposure, but it should be applicable to a wide variety of situations.
研究了一种用于解释变量的简单测量误差模型，该模型包含经典情况和伯克森情况作为特殊形式，并允许存在加性误差或乘性误差。这项工作的动机来自流行病学问题，因此不仅考虑了连续响应变量，还考虑了逻辑回归模型。还考虑了研究中不同个体具有不同类型误差的可能性。在各种误差结构的假设下，通过模拟检验了为队列数据和病例对照数据提出的相对简单的估计程序。结果表明，即使在传统分析得出的斜率估计值平均衰减约50%的情况下，使用所提出的修正似然函数获得的估计值也在其真实值的5%以内。开展这项工作是为了提供一种分析居住氡暴露后肺癌风险的方法，但它应该适用于多种情况。
