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首页> 外文期刊>Biometrika >THE ANALYSIS OF LONGITUDINAL ORDINAL DATA WITH NONRANDOM DROP-OUT
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THE ANALYSIS OF LONGITUDINAL ORDINAL DATA WITH NONRANDOM DROP-OUT

机译:非随机跳出的纵向常规数据分析

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摘要

A model is proposed for longitudinal ordinal data with nonrandom drop-out, which combines the multivariate Dale model for longitudinal ordinal data with a logistic regression model for drop-out. Since response and drop-out are modelled as conditionally independent given complete data, the resulting likelihood can be maximised relatively simply, using the EM algorithm, which with acceleration is acceptably fast and, with appropriate additions, can produce estimates of precision. The approach is illustrated with an example. Such modelling of nonrandom drop-out requires caution because the interpretation of the fitted models depends on assumptions that are unexaminable in a fundamental sense, and the conclusions cannot be regarded as necessarily robust. The main role of such modelling may be as a component of a sensitivity analysis. [References: 26]
机译:提出了具有非随机缺失的纵向序数数据模型,该模型将纵向序数数据的多元Dale模型与缺失的逻辑回归模型相结合。由于响应和遗漏被建模为条件独立的给定完整数据,因此使用EM算法可以相对简单地最大程度地提高结果似然性,该算法的加速度可以接受得很快,并且可以通过适当的加法来产生精度估计。举例说明该方法。这种对非随机缺失的建模需要谨慎,因为拟合模型的解释取决于在基本意义上无法辩驳的假设,因此不能认为结论必然具有鲁棒性。这种建模的主要作用可能是作为灵敏度分析的一部分。 [参考:26]

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