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

Overview of attention for article published in Psychonomic Bulletin & Review, February 2017
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Title
The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective
Published in
Psychonomic Bulletin & Review, February 2017
DOI 10.3758/s13423-016-1221-4
Pubmed ID
Authors

John K. Kruschke, Torrin M. Liddell

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.

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X Demographics

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Mendeley readers

Mendeley readers

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Geographical breakdown

Country Count As %
United States 4 <1%
Germany 2 <1%
Chile 2 <1%
Belgium 2 <1%
Italy 1 <1%
Brazil 1 <1%
Ireland 1 <1%
Colombia 1 <1%
Canada 1 <1%
Other 6 <1%
Unknown 1265 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 307 24%
Researcher 207 16%
Student > Master 142 11%
Student > Bachelor 93 7%
Student > Doctoral Student 84 7%
Other 241 19%
Unknown 212 16%
Readers by discipline Count As %
Psychology 385 30%
Agricultural and Biological Sciences 97 8%
Social Sciences 62 5%
Neuroscience 61 5%
Computer Science 51 4%
Other 332 26%
Unknown 298 23%