Deletion diagnostics for alternating logistic regressions.
Deletion diagnostics for alternating logistic regressions.
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DOI：
10.1002/bimj.201200002
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发表时间：
2012-09
影响因子：
1.7
通讯作者：
Qaqish, Bahjat F.
中科院分区：
文献类型：
--
作者：
Preisser, John S.;By, Kunthel;Perin, Jamie;Qaqish, Bahjat F.
关键词：
引入了删除诊断法，用于用交替Logistic回归估计的集群二元结果的回归分析，广义估计方程(GEE)的实现，其估计边际平均模型中的回归系数和由对数优势比给出的簇内关联的模型中的回归系数。诊断是在估计方程式框架内开发的，该估计方程式框架将基于条件残差的关联参数的估计函数重铸成基于边际残差的等价函数。GEE诊断学早期工作的扩展紧随其后，包括一步删除诊断法的计算公式，该公式衡量一组观测对估计回归参数和总体边际平均值或关联模型拟合度的影响。诊断公式通过模拟研究和关于初级保健医疗实践中与健康维护访问相关的因素评估的应用来评估。应用和仿真表明，所提出的交替Logistic回归的簇删除诊断方法是完全迭代的精确诊断方法的良好近似。
Deletion diagnostics are introduced for the regression analysis of clustered binary outcomes estimated with alternating logistic regressions, an implementation of generalized estimating equations (GEE) that estimates regression coefficients in a marginal mean model and in a model for the intracluster association given by the log odds ratio. The diagnostics are developed within an estimating equations framework that recasts the estimating functions for association parameters based upon conditional residuals into equivalent functions based upon marginal residuals. Extensions of earlier work on GEE diagnostics follow directly, including computational formulae for one-step deletion diagnostics that measure the influence of a cluster of observations on the estimated regression parameters and on the overall marginal mean or association model fit. The diagnostic formulae are evaluated with simulations studies and with an application concerning an assessment of factors associated with health maintenance visits in primary care medical practices. The application and the simulations demonstrate that the proposed cluster-deletion diagnostics for alternating logistic regressions are good approximations of their exact fully iterated counterparts.
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影响因子：
1.9
作者：
Lipsitz, SR;Fitamaurice, GM
通讯作者：
Fitamaurice, GM
影响因子：
2.7
作者：
Qaqish, BF
通讯作者：
Qaqish, BF
影响因子：
2.7
作者：
CAREY, V;ZEGER, SL;DIGGLE, P
通讯作者：
DIGGLE, P
DOI：
10.1111/j.1467-985x.2011.01003.x
发表时间：
2012-01-01
影响因子：
2
作者：
Reboussin, Beth A.;Preisser, John S.;Wolfson, Mark
通讯作者：
Wolfson, Mark
DOI：
10.1111/j.1467-9469.2012.00802.x
发表时间：
2012-09-01
期刊：
Scandinavian journal of statistics, theory and applications
影响因子：
--
作者：
Qaqish BF;Zink RC;Preisser JS
通讯作者：
Preisser JS