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Cross Validation Calibration Based Shrinkage – Revisited for the Construction of Prognostic Indices

机译：基于交叉验证标定的收缩率–重新用于构建预后指标

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摘要

The use of shrinkage methods for the construction of prognostic indices has been paid increasing attention in the literature on medical statistics in the last years. One approach for the construction of a shrinkage factor is cross validation calibration as suggested by van Houwelingen and le Cessie (1990). We investigate this approach in more detail. First we try to clarify why shrinkage factors constructed by cross validation calibration tend to be smaller than 1. Second we explain why use of this shrinkage factor can result in an improvement of the average prediction error. Third we investigate the possible gain for constellations relevant in medical research by means of a simulation study, focusing on the dilemma, that the improvement on average has to be paid by distinct deteriorations for some patients. Finally we conclude that it is necessary to rethink the choice of loss functions in constructing prognostic indices before recommendations about the use of shrinkage methods can be made.
机译：近年来，在医学统计文献中，越来越多地使用收缩方法来建立预后指标。 van Houwelingen和le Cessie（1990）提出了一种构建收缩因子的方法是交叉验证校准。我们将更详细地研究这种方法。首先，我们尝试阐明为什么通过交叉验证校准构建的收缩因子趋向于小于1。其次，我们解释了为何使用此收缩因子可以改善平均预测误差。第三，我们通过模拟研究来研究医学研究中相关星座的可能收益，重点是两难境地，即某些患者的平均改善必须由明显的恶化来支付。最后，我们得出结论，在提出使用收缩方法的建议之前，有必要重新考虑损失函数在构建预后指标中的选择。

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