Spatial regression models have grown in popularity in response to rapid advances in GIS (Geographic Information Systems) technology that allows epidemiologists to incorporate geographically indexed data into their studies. However, it turns out that there are some subtle pitfalls in the use of these models. We show that presence of covariate measurement error can lead to significant sensitivity of parameter estimation to the choice of spatial correlation structure. We quantify the effect of measurement error on parameter estimates, and then suggest two different ways to produce consistent estimates. We evaluate the methods through a simulation study. These methods are then applied to data on Ischemic Heart Disease (IHD).

中文翻译：

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协变量测量误差对空间回归建模的影响

随着 GIS（地理信息系统）技术的快速发展，空间回归模型越来越受欢迎，该技术允许流行病学家将地理索引数据纳入他们的研究。然而，事实证明，在使用这些模型时存在一些微妙的陷阱。我们表明协变量测量误差的存在会导致参数估计对空间相关结构选择的显着敏感性。我们量化了测量误差对参数估计的影响，然后提出了两种不同的方法来产生一致的估计。我们通过模拟研究评估这些方法。然后将这些方法应用于缺血性心脏病 (IHD) 的数据。