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Approximate subject-deletion influence diagnostics for Inverse Probability of Censoring Weighted (IPCW) method

机译:删失加权加权概率(IPCW)方法的近似主题删除影响诊断

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摘要

An approximate formula for subject-deletion influence diagnostics is proposed for the Inverse Probability of Censoring Weighted method [Robins, J.M., Rotnitzky, A., Zhao, P., 1995. Analysis of semiparametric regression models for repeated outcomes in the presence of missing data. J. Amer. Statist. Assoc. 90, pp. 106-121] when the independent working correlation is employed. By a numerical study with a dataset from a clinical trial, it is found that the formula provDEes good approximation to the exact method by fitting regression models repeatedly to datasets without each subject and saves the computational time remarkably in particular for large datasets.
机译:针对审查删失加权概率的反概率,提出了一种删除主题影响的诊断方法的近似公式[Robins,JM,Rotnitzky,A.,Zhao,P.,1995。在缺少数据的情况下对重复结果进行半参数回归模型的分析。 J.阿米尔。统计员。副会长90,pp。106-121]。通过对来自临床试验的数据集进行的数值研究发现,该公式通过将回归模型重复拟合到没有每个受试者的数据集而为精确方法提供了良好的近似,并且特别是对于大型数据集,显着节省了计算时间。

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