JASP has been updated! This is a maintenance release that contains the following improvements: Performance improvements on both Mac and Windows resulting from upgrades to our development framework (Qt 6.2, R 4.1.3) There is a new build for Apple Silicon (e.g., M1 iMacs and Macbooks) that makes use of Apple’s new chipset resulting in a significant speed up. The installation…
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‘How can we model the form of change in an outcome as time passes by?’, ‘Which statistical technique helps us to describe individual growth trajectory’s over time?’, ‘Can individual differences in an initial state and in change over time be analyzed?’ These questions are of importance to researchers who examine developmental, longitudinal, or consecutive measurements across multiple occasions. What solves…
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We are happy to announce that JASP 0.16.1 has been released and is now available on our download page. JASP 0.16.1 contains the following new features and improvements: JASP is now available in French (incomplete). The Machine Learning module has been expanded so that you can now perform (1) Support Vector Machine regression and classification analyses, and (2) Decision Tree…
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Researchers often have questions about inter-relationships between observed variables (indicators) and latent variables (factors). The Multiple Indicators and Multiple Causes (MIMIC) model is one of the models to quench the thirst for such questions! The latest JASP release provides MIMIC models as part of the SEM module. This tutorial introduces the idea of MIMIC models and, with a simple example,…
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Many research questions in the social and behavioral sciences rely on between-group comparisons of scores on scales from questionnaires. But how do we know that the questionnaire measures the same thing across different groups? Such comparisons require measurement invariance to be appropriate. Multi-group-Modeling, an analytical approach that belongs to the class of Structural Equation Modeling (SEM), provides the toolbox that…
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There are multiple statistical tests concerning a single parameter of interest such as t-test or a binomial test of proportions. Those tests can be performed with summary statistics that completely describe the observed data. In this new analysis, we extend the “Summary Statistics” module with a “General Bayesian Tests” analysis that allows us to evaluate the evidence in favor of…
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The 2nd annual JASP Users meeting will take place the 19th of May, 2022 from 14.00-16.30 Amsterdam time. This will be an online event with presentations on new & planned features, adding R packages, and free textbooks. For a detailed program and free registration see https://www.uu.nl/en/events/jasp-users-meeting.
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JASP has had a successful year in which it has become more user-friendly, accessible and flexible. We have released two new versions, numerous translations were added and the backend has been improved. Major developments of JASP in 2021 Simplifying JASP’s internal structure Behind the scenes, our developers have put a lot of effort into further developing JASP’s backend, that is,…
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We wish to reanalyze the BGC vaccine dataset that was used as evidence of a positive preventive effect of the BGC vaccine against tuberculosis. As in our previous blog post about PET-PEESE, we want to assess the effect of publication bias –a preferential publishing of statistically significant studies (Rosenthal & Gaito, 1964)– on the meta-analytic effect size estimate. In contrast…
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Source: shutterstock.com/szczygiel The analyses in this blog post are based on an example from Bartoš et al. (2021). Publication bias is a serious problem for meta-analyses that can lead to inflated effect size estimates. In order to adjust for and assess the effect of publication bias –a preferential publishing of statistically significant studies (Rosenthal & Gaito, 1964)– on the meta-analytic…
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Source: Getsnoopy, CC BY-SA 4.0, via Wikimedia Commons. In 1938 Frank Benford observed that in many natural occurring sets of numerical data (e.g., population numbers, death rates, stock prices) a leading “1” (30.1%) appears more frequently than a leading “2” (17.6%), which in turn appears more frequently than a leading “3” (12.5%) and so forth. The relative frequencies of these…
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