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The Bayesian Methodology of Sir Harold Jeffreys as a Practical Alternative to the PValue Hypothesis Test

Authors :
Ly, Alexander
Stefan, Angelika
van Doorn, Johnny
Dablander, Fabian
van den Bergh, Don
Sarafoglou, Alexandra
Kucharský, S̆imon
Derks, Koen
Gronau, Quentin F.
Raj, Akash
Boehm, Udo
van Kesteren, Erik-Jan
Hinne, Max
Matzke, Dora
Marsman, Maarten
Wagenmakers, Eric-Jan
Source :
Computational Brain & Behavior; June 2020, Vol. 3 Issue: 2 p153-161, 9p
Publication Year :
2020

Abstract

Despite an ongoing stream of lamentations, many empirical disciplines still treat the pvalue as the sole arbiter to separate the scientific wheat from the chaff. The continued reign of the pvalue is arguably due in part to a perceived lack of workable alternatives. In order to be workable, any alternative methodology must be (1) relevant: it has to address the practitioners’ research question, which—for better or for worse—most often concerns the test of a hypothesis, and less often concerns the estimation of a parameter; (2) available: it must have a concrete implementation for practitioners’ statistical workhorses such as the ttest, regression, and ANOVA; and (3) easy to use: methods that demand practitioners switch to the theoreticians’ programming tools will face an uphill struggle for adoption. The above desiderata are fulfilled by Harold Jeffreys’s Bayes factor methodology as implemented in the open-source software JASP. We explain Jeffreys’s methodology and showcase its practical relevance with two examples.

Details

Language :
English
ISSN :
25220861 and 2522087X
Volume :
3
Issue :
2
Database :
Supplemental Index
Journal :
Computational Brain & Behavior
Publication Type :
Periodical
Accession number :
ejs67140297
Full Text :
https://doi.org/10.1007/s42113-019-00070-x