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Hypothesis Testing p Values Confidence Intervals Measures of Effect Size and Bayesian Methods in Light of Modern Robust Techniques

机译:假设检验p值置信区间效应大小的度量以及根据现代稳健技术进行的贝叶斯方法

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摘要

The article provides perspectives on p values, null hypothesis testing, and alternative techniques in light of modern robust statistical methods. Null hypothesis testing and p values can provide useful information provided they are interpreted in a sound manner, which includes taking into account insights and advances that have occurred during the past 50 years. There are, of course, limitations to what null hypothesis testing and p values reveal about data. But modern advances make it clear that there are serious limitations and concerns associated with conventional confidence intervals, standard Bayesian methods, and commonly used measures of effect size. Many of these concerns can be addressed using modern robust methods.
机译:本文根据现代稳健的统计方法提供了有关p值,原假设检验和替代技术的观点。空假设检验和p值可以提供有用的信息,前提是它们能以合理的方式进行解释,包括考虑过去50年中发生的见解和进展。当然,对原假设检验和p值揭示的数据有限制。但是现代的进步清楚地表明,与常规置信区间,标准贝叶斯方法以及常用的效应量度相关联,存在着严重的局限性和担忧。使用现代可靠的方法可以解决许多这些问题。

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