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Outlier detection in logistic regression and its application in medical data analysis

机译:Logistic回归中的异常值检测及其在医学数据分析中的应用

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摘要

The application of logistic regression is widely used in medical research. The detection of outliers has become an essential part of logistic regression. It is often observed outliers have a considerable influence on the analysis results, which may lead the study to the wrong conclusions. Many procedures for the identification of outliers in logistic regression are available in the literature. In this paper, four methods for outlier detection have been investigated and compared through numerical examples.
机译:Logistic回归的应用已广泛用于医学研究。离群值的检测已成为逻辑回归的重要部分。经常观察到离群值对分析结果有相当大的影响,这可能导致研究得出错误的结论。文献中提供了许多用于在逻辑回归中识别异常值的程序。本文研究了四种离群值检测方法,并通过数值算例进行了比较。

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