Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA.
Comput Methods Programs Biomed. 2014 Feb;113(2):557-68. doi: 10.1016/j.cmpb.2013.09.017. Epub 2013 Oct 31.
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.
本文介绍了一种基于正交残差的新的相关二项数据建模软件，这是一种最近开发的估计方程方法，包括作为特例的交替逻辑回归。该软件在拟合方面具有灵活性，用户可以选择基于交替逻辑回归或正交残差的关联模型的估计方程，后者选择为二阶矩参数提供非对角工作协方差矩阵，从而提供潜在的更高效率。该软件还实现了基于这种方法的回归诊断。简要回顾了数学背景，并将该软件应用于医学数据集。
