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To t-Test or Not to t-Test? A p-Values-Based Point of View in the Receiver Operating Characteristic Curve Framework

机译:要进行t检验还是不进行t检验?接收机工作特性曲线框架中基于p值的观点

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摘要

>A common statistical doctrine supported by many introductory courses and textbooks is that t-test type procedures based on normally distributed data points are anticipated to provide a standard in decision-making. In order to motivate scholars to examine this convention, we introduce a simple approach based on graphical tools of receiver operating characteristic (ROC) curve analysis, a well-established biostatistical methodology. In this context, we propose employing a p-values-based method, taking into account the stochastic nature of p-values. We focus on the modern statistical literature to address the expected p-value (EPV) as a measure of the performance of decision-making rules. During the course of our study, we extend the EPV concept to be considered in terms of the ROC curve technique. This provides expressive evaluations and visualizations of a wide spectrum of testing mechanisms' properties. We show that the conventional power characterization of tests is a partial aspect of the presented EPV/ROC technique. We desire that this explanation of the EPV/ROC approach convinces researchers of the usefulness of the EPV/ROC approach for depicting different characteristics of decision-making procedures, in light of the growing interest regarding correct p-values-based applications.
机译:>许多入门课程和教科书都支持一种常见的统计学说,即基于正态分布数据点的t检验类型程序有望为决策提供标准。为了激励学者们研究这一惯例,我们引入了一种基于接收器工作特性(ROC)曲线分析的图形工具的简单方法,这是一种公认​​的生物统计学方法。在这种情况下,考虑到p值的随机性,我们建议采用基于p值的方法。我们关注于现代统计文献,以处理预期的p值(EPV)作为衡量决策规则性能的指标。在我们的研究过程中,我们扩展了EPV概念,以考虑ROC曲线技术。这提供了广泛的测试机制特性的表达性评估和可视化。我们表明测试的常规功率表征是提出的EPV / ROC技术的部分内容。鉴于对基于p值的正确应用的关注日益增长,我们希望对EPV / ROC方法的这种解释使研究人员相信EPV / ROC方法在描述决策过程的不同特征方面的有用性。

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