A Hack for Editing JASP Graphs

From JASP 0.13 onwards, it is possible to save JASP graphs “as pptx”, courtesy of the R package “officer”. The resulting .pptx file can then be easily edited in Powerpoint or its open-source cousin Impress. Hence, “save as pptx” offers a new opportunity to edit JASP graphs. Obviously this is a temporary patch and not the ultimate solution; full graph…

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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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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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Mediation and Moderation Analysis in JASP

Over the past few years, we’ve found that mediation and moderation analysis are highly requested features. Since version 0.10.1, JASP can do both! This blogpost goes through two introductory examples, showing how mediation and moderation can be performed in JASP. Mediation means that the effect of a variable X on variable Y is (partially) indirect, through the variable M. Moderation…

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How a Simple Bayesian Test Could Have Rescued a Famous Clinical Trial

One of the features that we have recently added to JASP is a Bayesian “A/B test”, that is, a test for the equality of two binomial proportions. This test is especially popular in the analysis of clinical trial data, where the proportion of medical successes (or failures) from a treatment group is contrasted against those from a control group. The…

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Introducing a New JASP-Fueled Textbook: Learning Statistics with JASP

I am proud to announce the release of our free textbook Learning Statistics with JASP: A Tutorial for Psychology Students and Other Beginners by Danielle J. Navarro, David R. Foxcroft, and Thomas J. Faulkenberry. This textbook, which is freely downloadable from https://learnstatswithjasp.com, continues the series of open-source adaptations of the popular text Learning Statistics with R by Danielle Navarro. Learning…

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