ORTH: R and SAS software for regression models of correlated binary data based on orthogonalized residuals and alternating logistic regressions |
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| Authors: | Kunthel By Bahjat F. Qaqish John S. Preisser Jamie Perin Richard C. Zink |
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| Affiliation: | 1. Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA;2. Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, MD, USA;3. JMP Life Sciences, SAS Institute Inc., NC, USA |
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| Abstract: | 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. |
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| Keywords: | Association models Estimating equations Logistic regression Permutation invariance Regression diagnostics |
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