Frequentist and Bayesian Equivalence Testing in JASP

This post demonstrates the Equivalence Testing Module, new in JASP 0.12. In traditional hypothesis testing, both frequentist and Bayesian, the null hypothesis is often specified as a point (i.e., there is no effect whatsoever in the population). Consequently, in very large samples, small but practically meaningless deviations from the point-null will lead to its rejection. In order to take into…

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JASP for Education and Research; A Pilot Project at Utrecht University

At Utrecht University JASP is increasingly used by lecturers in statistics courses and by thesis students and researchers for the (Bayesian) evaluation of their data. To contribute to the further development of JASP and to facilitate its use at Utrecht University a pilot project has started executed by scientists from Utrecht University. Core features of this project are: the addition…

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Bayesian Inference in JASP: A New Guide For Students

Mark Goss-Sampson’s popular manual “Statistical analysis with JASP: A guide for students” has now been followed up by a new guide that focuses on Bayesian inference. The guide first introduces the JASP interface and data handling procedures, and then outlines the Bayesian terminology together with an explanation of the different plots that are typically produced by the analyses. Next, the…

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Improved Annotations in JASP 0.12, Demonstrated with a Bayesian Meta-Analysis of Kristal et al., 2020

The goal of this JASP blog post is threefold: To demonstrate the improved ability to annotate analyses. For annotations, JASP 0.12 now uses Quill. As stated on https://quilljs.com/, “Quill is a free, open source WYSIWYG editor built for the modern web. With its modular architecture and expressive API, it is completely customizable to fit any need.“ To demonstrate the ease…

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How to Conduct a Bayesian Model-Averaged Meta-Analysis in JASP

JASP 0.12 brings Bayesian meta-analysis! Based on the metaBMA package (Heck, Gronau & Wagenmakers, 2019), JASP now includes Bayesian model-averaged meta-analysis so you no longer have to make an all-or-none choice between fixed and random effects models. Additionally, a constrained random effects approach is implemented which answers the question whether every study shows an effect in the same, expected direction.…

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Webinar: Theory and Practice of Bayesian Inference Using JASP

In June, 2019, three JASP team members (Alexander Etz, Julia Haaf, and Johnny van Doorn) taught a webinar on Bayesian inference for The Society for Personality and Social Psychology. The webinar provides a gentle introduction to Bayesian statistics and demonstrates how to perform Bayesian analyses using JASP. The video is structured as follows: Bayesian basics Bayesian hypothesis testing and the…

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JAGS Meets JASP

Data from the reproducibility project. The x-axis shows the effect size of the original studies, the y-axis shows the effect size of the replications. The color indicates whether a replication was significant (purple) or not (black). A linear regression line is fit for each group. Figure from JASP. If there is one thing that caused widespread adoption of Bayesian inference,…

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The Visual Modeling Module

This is a guest post by Dustin Fife, responsible for the Visual Modeling module in JASP. Years ago when I worked as a biostatistician, I was assigned to analyze the data for a local luminary in the field of Muscular Sclerosis. This analysis would lead to a conference submission, at least, and likely a publication. The man provided me a…

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Discover Distributions in JASP

Probability distributions lie at the heart of most statistical analyses and thus are crucial for proper understanding and use of statistics. To help researchers, students, and lecturers work easily with various probability distributions, we created the ‘Distribution’ module which is one of the new features of the upcoming version of JASP. As of now, JASP currently covers 12 basic distributions,…

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The Wonderful World of Marginal Means

This post was inspired by a conversation I had with Henrik Singmann, maintainer of the glorious afex package. The latest iteration of JASP, version 0.12, features a much sought after functionality in ANOVA’s: specifying custom contrasts! This development sparked a lively discussion with some team members about the available options when following up on a detected main effect in an…

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