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Sample size calculation for method validation using linear regression

机译:使用线性回归计算样本量以进行方法验证

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摘要

In this article, we present a method for sample size calculation for studies involving both the intercept and slope parameters of a simple linear regression model. Some methods have been proposed in the literature to determine the adequate sample size. However, they are usually based on the line slope only. We propose a method based on the F statistic that involves both the intercept and the slope parameters of the model. The validation process is conducted by fitting a simple linear regression model and by testing a zero intercept and unity slope hypothesis. Compared to a traditional method and using Monte Carlo simulations, encouraging results attest for the clear superiority of the proposed method. The article ends with a real-life example showing the value of the new method in practice.
机译:在本文中,我们提出了一种用于样本量计算的方法,用于涉及简单线性回归模型的截距和斜率参数的研究。文献中已经提出了一些方法来确定适当的样本量。但是,它们通常仅基于直线斜率。我们提出了一种基于F统计量的方法,该方法同时涉及模型的截距和斜率参数。通过拟合简单的线性回归模型并测试零截距和统一斜率假设来进行验证过程。与传统方法相比,并使用蒙特卡洛模拟,令人鼓舞的结果证明了该方法的明显优势。本文以一个真实的示例结尾,展示了该新方法在实践中的价值。

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