Discussion points for Bayesian inference

Author:

Aczel BalazsORCID,Hoekstra RinkORCID,gelman andrewORCID,Wagenmakers Eric-JanORCID,Klugkist Irene,Rouder Jeffrey N.,Vandekerckhove JoachimORCID,Lee Michael DavidORCID,Morey Richard DonaldORCID,vanpaemel wolf,Dienes Zoltan,van Ravenzwaaij DonORCID

Abstract

Despite its many advocates, Bayesian inference is currently employed by only a minority of social and behavioural scientists. One possible barrier is a lack of consensus on how best to conduct and report such analyses. Employing Bayesian methods involves making choices about prior distributions, likelihood functions and robustness checks, as well as about how to present, visualize and interpret the results (for a glossary of the main Bayesian statistical concepts, see Box 1). Some researchers may find this wide range of choices too daunting to use Bayesian inference in their own study. This paper highlights the areas of agreement and the arguments behind disagreements, established on the back of a self-questionnaire provided and explained in detail on OSF (https://osf.io/6eqx5/).

Publisher

Center for Open Science

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