Cologne J B, Carter R L, Fujita S, Ban S
Department of Statistics, Radiation Effects Research Foundation, Hiroshima, Japan.
Biometrics. 1993 Sep;49(3):927-34.
We describe an application of the generalized estimating equation (GEE) method (Liang and Zeger, 1986, Biometrika 73, 13-22) for regression analysis of correlated Poisson data from a split-plot design with a small number of experimental units. As an alternative to the use of an arbitrarily chosen working correlation matrix, we demonstrate the use of GEE with a reasonable model for the true covariance structure among repeated observations within individuals. We show that, under such a split-plot design with large clusters, the asymptotic relative efficiency of GEE with simple (independence or exchangeable) working correlation matrices is rather low. We conclude by summarizing issues and needs for further work concerning efficiency of the GEE parameter estimates in practice.
我们描述了广义估计方程（GEE）方法（Liang和Zeger，1986年，《生物统计学》73卷，第13 - 22页）在具有少量实验单元的裂区设计相关泊松数据回归分析中的应用。作为使用任意选择的工作相关矩阵的替代方法，我们展示了如何将GEE与个体内重复观测值之间真实协方差结构的合理模型结合使用。我们表明，在这种具有大聚类的裂区设计下，使用简单（独立或可交换）工作相关矩阵的GEE的渐近相对效率相当低。我们通过总结关于GEE参数估计在实际应用中的效率的进一步研究问题和需求来结束本文。
