GEECAT and GEEGOR: computer programs for the analysis of correlated categorical response data.
GEECAT and GEEGOR: computer programs for the analysis of correlated categorical response data.
复制标题
GEECAT 和 GEEGOR：用于分析相关分类响应数据的计算机程序。
DOI：
10.1016/s0169-2607(98)00063-7
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发表时间：
1999
影响因子：
6.1
通讯作者：
Kim,KM
中科院分区：
文献类型：
--
作者：
Williamson,JM;Lipsitz,SR;Kim,KM
GEECAT和GEEGOR是两个用户友好的SAS宏，用于分析聚类的相关分类响应数据。这两个程序执行的方法扩展了Liang和Zeger（Biometrika 73（1986）13-22）的广义估计方程（GEE）方法。GEECAT和GEEGOR都使用第一组估计方程来模拟边际响应。使用GEECAT，可以分析相关的名义或有序分类响应数据。程序GEEGOR采用第二组估计方程，以全局优势比作为关联度量，对聚类内有序分类响应的关联进行建模。这些程序在大型计算机和微型计算机上运行。提供的例子来说明这两个程序的功能。
GEECAT and GEEGOR are two user-friendly SAS macros for the analysis of clustered, correlated categorical response data. Both programs implement methodology which extend the generalized estimating equation (GEE) approach of Liang and Zeger (Biometrika 73 (1986) 13–22). GEECAT and GEEGOR both use a first set of estimating equations to model the marginal response. With GEECAT, either correlated nominal or ordered categorical response data can be analyzed. The program GEEGOR employs a second set of estimating equations to model the association of ordered categorical responses within a cluster using the global odds ratio as a measure of association. The programs run on both mainframe computers and microcomputers. Examples are provided to illustrate the features of both programs.