Goodness-of-fit tests for GEE modeling with binary responses
Goodness-of-fit tests for GEE modeling with binary responses
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DOI：
10.2307/3109778
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发表时间：
1998-06-01
期刊：
影响因子：
1.9
通讯作者：
Williamson, JM
中科院分区：
文献类型：
--
作者：
Barnhart, HX;Williamson, JM
重复测量数据的分析通常是通过使用广义估计方程(GEE)方法来完成的。虽然存在用似然方法评估不相关数据的拟合模型的充分性的方法，但对于用GEE方法拟合的模型来说，使用这些方法是不合适的。通过将协变量空间划分为不同的区域，形成分数统计量，并将其渐近分布为具有适当自由度的卡方随机变量，我们提出了基于模型和稳健(经经验校正)的二元响应GEE建模的拟合优度检验。使用模拟数据对拟合度检验的零分布和统计能力进行了评估。两个使用临床研究数据的例子说明了所提出的拟合度检验。
Analysis of data with repeated measures is often accomplished through the use of generalized estimating equations (GEE) methodology. Although methods exist for assessing the adequacy of the fitted models for uncorrelated data with likelihood methods, it is not appropriate to use these methods for models fitted with GEE methodology. We propose model-based and robust (empirically corrected) goodness-of-fit tests for GEE modeling with binary responses based on partitioning the space of covariates into distinct regions and forming score statistics that are asymptotically distributed as chi-square random variables with the appropriate degrees of freedom. The null distribution and the statistical power of the proposed goodness-of-fit tests were assessed using simulated data. The proposed goodness-of-fit tests are illustrated by two examples using data from clinical studies.