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贝叶斯推断在心理学中的应用。第一部分:理论优势与实际影响。

Bayesian inference for psychology. Part I: Theoretical advantages and practical ramifications.

机构信息

Department of Psychological Methods, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018 VZ, Amsterdam, The Netherlands.

Masaryk University, Brno, Czech Republic.

出版信息

Psychon Bull Rev. 2018 Feb;25(1):35-57. doi: 10.3758/s13423-017-1343-3.

Abstract

Bayesian parameter estimation and Bayesian hypothesis testing present attractive alternatives to classical inference using confidence intervals and p values. In part I of this series we outline ten prominent advantages of the Bayesian approach. Many of these advantages translate to concrete opportunities for pragmatic researchers. For instance, Bayesian hypothesis testing allows researchers to quantify evidence and monitor its progression as data come in, without needing to know the intention with which the data were collected. We end by countering several objections to Bayesian hypothesis testing. Part II of this series discusses JASP, a free and open source software program that makes it easy to conduct Bayesian estimation and testing for a range of popular statistical scenarios (Wagenmakers et al. this issue).

摘要

贝叶斯参数估计和贝叶斯假设检验为使用置信区间和 p 值进行经典推理提供了有吸引力的替代方法。在本系列的第一部分,我们概述了贝叶斯方法的十个突出优点。其中许多优点转化为实际研究人员的具体机会。例如,贝叶斯假设检验允许研究人员在数据输入时量化证据并监测其进展,而无需知道收集数据的意图。最后,我们反驳了对贝叶斯假设检验的几个反对意见。本系列的第二部分讨论了 JASP,这是一个免费和开源的软件程序,它使得在一系列流行的统计场景中进行贝叶斯估计和检验变得非常容易(Wagenmakers 等人,本期)。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d559/5862936/3290189c8d16/13423_2017_1343_Fig1_HTML.jpg

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