Time Series Forecasting: Introduction to the Prophet Module in JASP

We are happy to present JASP’s first procedure for time series analysis! Version 0.15 includes the Prophet module which contains the homonymous analysis developed by Facebook’s Taylor and Letham (2018). Its core feature is a model that allows flexible time series forecasting on different scales. You want time series visualization? Changepoint estimation? Does your time series data have strong seasonalities?…

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How to Install JASP on Your Chromebook

All Chromebooks that came out in 2019 or later explicitly support Linux and therefore allow JASP to be installed. Certain older models might also have this capability. To find out if your Chromebook supports Linux, go to “Settings” and look for the “Linux (Beta)” option. It should look something like this: If you do not see this entry then your…

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Learn Bayes with Binomial Estimation in JASP

When students are first confronted with Bayesian statistics they have to become familiar with key concepts that differ fundamentally from those that they were taught in frequentist courses. To assist the transition to Bayesian inference we recently created the “Learn Bayes” module in JASP (with support from a grant from the APS Fund for Teaching and Public Understanding of Psychological…

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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 users work easily with various probability distributions, we created the ‘Distribution’ module. As of now, JASP currently covers 12 basic distributions, each available as a stand alone analysis panel: Continuous Normal Student’s t F-distribution Chi-squared Beta Gamma…

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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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