Chang Y C
Department of Mathematics, Tamkang University, Taipei, Taiwan 25137, R.O.C.
Stat Med. 2000 May 30;19(10):1277-93. doi: 10.1002/(sici)1097-0258(20000530)19:10<1277::aid-sim494>3.0.co;2-s.
The generalized estimation equation (GEE) method, one of the generalized linear models for longitudinal data, has been used widely in medical research. However, the related sensitivity analysis problem has not been explored intensively. One of the possible reasons for this was due to the correlated structure within the same subject. We showed that the conventional residuals plots for model diagnosis in longitudinal data could mislead a researcher into trusting the fitted model. A non-parametric method, named the Wald-Wolfowitz run test, was proposed to check the residuals plots both quantitatively and graphically. The rationale proposedin this paper is well illustrated with two real clinical studies in Taiwan.
广义估计方程（GEE）方法是纵向数据广义线性模型之一，已在医学研究中广泛应用。然而，相关的敏感性分析问题尚未得到深入探讨。造成这种情况的一个可能原因是同一受试者内部的相关结构。我们表明，纵向数据中用于模型诊断的传统残差图可能会误导研究人员相信拟合模型。我们提出了一种非参数方法，即Wald-Wolfowitz游程检验，用于从定量和图形两方面检查残差图。本文提出的基本原理在台湾的两项实际临床研究中得到了很好的说明。
