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贝叶斯新统计:从贝叶斯视角看假设检验、估计、元分析和功效分析。

The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective.

机构信息

Indiana University, Bloomington, USA.

出版信息

Psychon Bull Rev. 2018 Feb;25(1):178-206. doi: 10.3758/s13423-016-1221-4.

Abstract

In the practice of data analysis, there is a conceptual distinction between hypothesis testing, on the one hand, and estimation with quantified uncertainty on the other. Among frequentists in psychology, a shift of emphasis from hypothesis testing to estimation has been dubbed "the New Statistics" (Cumming 2014). A second conceptual distinction is between frequentist methods and Bayesian methods. Our main goal in this article is to explain how Bayesian methods achieve the goals of the New Statistics better than frequentist methods. The article reviews frequentist and Bayesian approaches to hypothesis testing and to estimation with confidence or credible intervals. The article also describes Bayesian approaches to meta-analysis, randomized controlled trials, and power analysis.

摘要

在数据分析实践中,一方面存在假设检验,另一方面存在量化不确定性的估计,这两者之间存在概念上的区别。在心理学中的频率主义者中,从假设检验到估计的重点转移被称为“新统计”(Cumming 2014)。第二个概念上的区别是在频率主义方法和贝叶斯方法之间。我们本文的主要目标是解释贝叶斯方法如何比频率主义方法更好地实现新统计的目标。本文回顾了假设检验和置信区间或可信区间估计的频率主义和贝叶斯方法。本文还描述了贝叶斯方法在荟萃分析、随机对照试验和功效分析中的应用。

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