JASP 0.14.1 – Minor Update

We are happy that JASP 0.14 has been downloaded over 99877 times since its release on October 14th! JASP 0.14.1 adds some improvements and fixes small issues. Some of the improvements are: Several changes to the audit module Evaluate audit samples more efficiently #4411 More prior construction methods #700 UVB functionality #1149 More computing speed for RoBMA #4408 Previously the…

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How to do Bayesian Linear Regression in JASP – A Case Study on Teaching Statistics

This is a guest post by Tom Faulkenberry (Tarleton State University). Click here to access the supplementary materials. Amid the COVID-19 pandemic, universities have needed to quickly adjust their traditional methods of instruction to allow for maximum flexibility. This means that professors have also had to think critically about how they can best deliver instruction in new formats. Ever the…

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Learn Bayes with Binomial Testing in JASP

To facilitate 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 Science). The goal of this module is to illustrate all steps of Bayesian parameter estimation and testing. In the previous blogpost we outlined the Binomial Estimation analysis, which…

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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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How To Compute Signal Detection Theory Functions in JASP- A Case Study

This is a guest post by Calvin Deans-Browne (UCL) and Henrik Singmann (UCL). Click here to access the supplemental materials. The Setup This article contains an introduction to the different indices measured in the signal detection theory (SDT) framework, a case study to put them into context, and how to compute them in JASP. An Introduction to SDT Indices Signal…

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Accounting for Publication Bias with Robust Bayesian Meta-Analysis in JASP

JASP 0.14 brings robust Bayesian meta-analysis (RoBMA). This extension of Bayesian meta-analysis allows researchers to adjust for publication bias when conducting model-averaged meta-analysis. RoBMA applies a set of twelve models simultaneously, some assuming publication bias and some assuming no publication bias. The inference will then be based most strongly on the models that predicted the data best. In other words,…

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JASP 0.14 – Now Available in German

JASP 0.14 has been released and is now available on our download page. JASP 0.14 contains the following new features and improvements: Publication bias-adjusted meta-analysis. JASP version 0.14 adds frequentist selection models as well as Robust Bayesian meta-analysis to correct for publication bias. Head over to our tutorial videos and a tutorial paper to learn how to use these analyses.…

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A Sneak Peek at JASP 0.14

JASP 0.14 will offer important new functionality, including: Robust Bayesian meta-analysis; Selection models; Learn Bayes module; PDF export of result; Choose your font; German translation; Frequentist partial correlations; Confidence and prediction intervals in linear regression; And new distributions in the distributions module (log-normal and logistic). Stay tuned for JASP 0.14! Out soon.

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Theory and Practice of Bayesian Hypothesis Testing: An Online JASP Workshop

This is an update regarding the JASP summer workshop “Theory and Practice of Bayesian Hypothesis Testing” scheduled for August 24-25, 2020. Due to the pandemic, the workshop will take place online. However, we aim to make use of a number of tools to create a smooth, fun, and interactive learning experience. Lectures will be held on Zoom, and video recordings…

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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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JASP 0.13.1: Small fixes

JASP 0.13.1 fixes several small issues. Specifically: Previously, our new “save as powerpoint” option for figures did not work on MacOS. Now it does. For some time, JASP was unstable on MacOS with Intel Iris GPU. This has now been fixed. Windows users with a “foreign” character in their username experienced problems. We have resolved this. A bug concerning changing…

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