A tutorial on Bayes Factor Design Analysis using an informed prior.

Authors:
Quentin F Gronau
Quentin F Gronau
University of Amsterdam
Netherlands
Eric-Jan Wagenmakers
Eric-Jan Wagenmakers
University of Amsterdam
Netherlands

Behav Res Methods 2019 Feb 4. Epub 2019 Feb 4.

Department of Psychology, Faculty of Behavioral and Social Sciences, University of Amsterdam, Nieuwe Achtergracht 129-B, 1018WS, Amsterdam, The Netherlands.

Well-designed experiments are likely to yield compelling evidence with efficient sample sizes. Bayes Factor Design Analysis (BFDA) is a recently developed methodology that allows researchers to balance the informativeness and efficiency of their experiment (Schönbrodt & Wagenmakers, Psychonomic Bulletin & Review, 25(1), 128-142 2018). With BFDA, researchers can control the rate of misleading evidence but, in addition, they can plan for a target strength of evidence. BFDA can be applied to fixed-N and sequential designs. In this tutorial paper, we provide an introduction to BFDA and analyze how the use of informed prior distributions affects the results of the BFDA. We also present a user-friendly web-based BFDA application that allows researchers to conduct BFDAs with ease. Two practical examples highlight how researchers can use a BFDA to plan for informative and efficient research designs.

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Source
http://dx.doi.org/10.3758/s13428-018-01189-8DOI Listing
February 2019

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References

(Supplied by CrossRef)
Article in BMJ
DG Altman et al.
BMJ 1995
Article in Psychological Science
M Bakker et al.
Psychological Science 2016

J Berger et al.
1985
Article in Bayesian Analysis
J Berger et al.
Bayesian Analysis 2006
Article in International Statistical Review / Revue Internationale de Statistique
JM Bernardo et al.
International Statistical Review / Revue Internationale de Statistique 2002

J Cohen et al.
1988
Article in Current Directions in Psychological Science
J Cohen et al.
Current Directions in Psychological Science 1992
Article in Frontiers in Psychology
Z Dienes et al.
Frontiers in Psychology 2014
Article in Controlled Clinical Trials
WD Dupont et al.
Controlled Clinical Trials 1990

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