ORTH: R and SAS software for regression models of correlated binary data based on orthogonalized residuals and alternating logistic regressions

被引:4
|
作者
By, Kunthel [1 ]
Qaqish, Bahjat F. [1 ]
Preisser, John S. [1 ]
Perin, Jamie [2 ]
Zink, Richard C. [3 ]
机构
[1] Univ N Carolina, Dept Biostat, Gillings Sch Global Publ Hlth, Chapel Hill, NC USA
[2] Johns Hopkins Univ, Bloomberg Sch Publ Hlth, Dept Int Hlth, Baltimore, MD 21218 USA
[3] SAS Inst Inc, JMP Life Sci, Cary, NC USA
基金
美国国家卫生研究院;
关键词
Association models; Estimating equations; Logistic regression; Permutation invariance; Regression diagnostics; GENERALIZED ESTIMATING EQUATIONS; WORKING CORRELATION MATRIX; DELETION DIAGNOSTICS; ASSOCIATION; PARAMETERS; TRIALS;
D O I
10.1016/j.cmpb.2013.09.017
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
This article describes a new software for modeling correlated binary data based on orthogonalized residuals, a recently developed estimating equations approach that includes, as a special case, alternating logistic regressions. The software is flexible with respect to fitting in that the user can choose estimating equations for association models based on alternating logistic regressions or orthogonalized residuals, the latter choice providing a non-diagonal working covariance matrix for second moment parameters providing potentially greater efficiency. Regression diagnostics based on this method are also implemented in the software. The mathematical background is briefly reviewed and the software is applied to medical data sets. Published by Elsevier Ireland Ltd.
引用
收藏
页码:557 / 568
页数:12
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