用于模型比较的经过修订的 Passing-Bablok 回归方法

N. Erilli
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引用次数: 0

摘要

第二类回归模型用于比较不止一种进行相同测量的方法。Passing-Bablok 回归法是其中的一种,它是非参数法,与其他比较方法相比,尤其是在存在异常值的情况下,可以得到更成功的结果。本研究对传统 Passing-Bablok 方法中使用的斜率和截距参数的计算方法进行了创新。我们建议使用特里曼参数来代替经典模型中使用的中位数参数,并对模型参数估计进行了相应的调整。在 15 个不同的数据集(其中 8 个是模拟数据集)上比较了所提出的新模型和经典模型的预测结果。结果表明,拟议的新模型计算结果比传统方法的结果误差更小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Revised Passing-Bablok Regression Method for Model Comparison
Type-II regression models are used to compare more than one method that makes the same measurement. The Passing-Bablok regression method, which is one of them, is non-parametric and can give more successful results than other comparison methods, especially when there are outliers. In this study, innovations in the calculations of slope and intercept parameters used in the traditional Passing-Bablok method are proposed. Instead of the median parameter used in the classical model, the use of the trimean parameter was suggested and the model parameter estimates were adjusted accordingly. The proposed new model and classical model predictions were compared on 15 different data sets, 8 of which were simulations. It has been determined that the proposed new model calculations contain fewer errors than the results of the classical method.
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