Meta-analysis in JASP

The JASP meta-analysis module was supported by a SSMART grant from the Berkeley Initiative for Transparency in the Social Sciences (BITSS), an initiative of the Center for Effective Global Action (CEGA). The new release of JASP supports an extensive arrange of commonly used techniques for meta-analysis. These include fixed and random effects analysis, fixed and mixed effects meta-regression, forest and…

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Announcing JASP 0.8.4: Meta-Analysis, Network Models, and More

The JASP team is happy to announce version 0.8.4. Here’s a select list of new features: A meta-analysis module; A network analysis module; Improved module layout; Stepwise methods for logistic regression; Effect size measures for post-hoc analyses in ANOVA/ANCOVA. In our next post we will take a closer look at the new functionality. For now, enjoy the new version! Like…

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Interview with a Team Member: Johnny van Doorn

In our series Interview With A Team Member, we aim to introduce the people behind the JASP-project. Today we are interviewing Johnny van Doorn, one of our analysts. Johnny van Doorn is a PhD candidate at the Psychological Methods department of the University of Amsterdam. At JASP, he is responsible for Bayesian nonparametric analyses. To contact Johnny, you can send…

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JASP vs. SPSS

The first version of SPSS was published 59 years ago. The first version of JASP was published three years ago. How does an expensive IBM-developed program compare to the free and open source program which was until recently just developed by a handful of scientists? My approach for this review is as a university lecturer in psychology. Ease of learning…

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How to Test Interval-Null Hypotheses in JASP

As discussed on the Bayesian Spectacles blog, some statisticians have an visceral dislike of the point-null hypothesis, fueled in part by the conviction that the point-null is never true. Back in 1938, Berkson (pp. 526-527) already summarized the argument: “I believe that an observant statistician who has had any considerable experience with applying the chi-square test repeatedly will agree with…

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How to Do a Hierarchical Regression in JASP

The latest JASP version, 0.8.3, introduced a plethora of new features, including hierarchical regression. This blog post briefly describes this analysis. In traditional linear regression, predictors are selected that form a statistical model; this model is then compared to the null model that includes only the intercept term. Performance of the specified model is then assessed by metrics such as…

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Just Out: JASP 0.8.3 — More Bang for No Bucks

We are happy to report that JASP 0.8.3 is now ready for download. Some of the new features have already been discussed in our previous post. Specifically, JASP 0.8.3 now includes logistic regression, hierarchical regression (i.e., the stepwise addition of predictors), a progress bar, and much more. Improvements in 0.8.3 Added logistic regression Added hierarchical regression Added progress bar to…

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Soon to Appear in JASP: Logistic Regression, Hierarchical Regression, Progress Bars, and More

The JASP team is in the final stages of testing the upcoming version, which is scheduled for release next week. The upcoming version, 0.8.3., contains many new features. My personal favorites: JASP 0.8.3 includes frequentist logistic regression (hat tip to the hmeasure R package for the confusion matrix diagnostics; Anagnostopoulos, Hand, & Adams, 2012). Kudos to Erik-Jan van Kesteren for…

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Tukey’s Lament: Are Statisticians Living a Lie?

John Tukey is famous. In his youth he coined the term “bit” (as an abbreviation of “binary information digit”), later he promoted exploratory data analysis, and throughout his entire life he worked on a broad range of statistical techniques, some of which carry his name. In 1991, Tukey published the article “The philosophy of multiple comparisons”. The paper starts with…

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