Multiple Indicators Multiple Causes (MIMIC) Model in JASP

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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Measurement Invariance Testing Using the Structural Equation Modeling (SEM) Module in JASP

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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New in JASP 0.16: Zoltan Dienes’ General Bayesian Tests

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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Join the 2nd JASP Users Meeting, Online, May 19th

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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Highlights of JASP in 2021

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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Using JASP to Adjust for Publication Bias with WAAP-WLS

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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Using JASP to Adjust for Publication Bias with PET-PEESE

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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Benford’s Law: Using JASP to Test Whether a Data Set Occurred Naturally

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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JASP已上线简体中文版

近期我们已将JASP翻译为简体中文。我们翻译了用户界面,结果报告页面,统计分析界面等。未来我们也希望能慢慢完成剩余部分的翻译。因为JASP一直都在添加和完善新的功能,它的翻译会是一个长期的过程。如果你想成为我们翻译团队的一员,请前往JASP的翻译托管页面:(https://hosted.weblate.org/languages/zh_Hans/jasp/)。获取有关翻译步骤的指导请邮件shuonwang@gmail.com,或前往:(https://jasp-stats.org/translation-guidelines/)。   非常开心JASP简体中文版已经上线,希望这个版本能让中文母语的同胞们更加容易地学习、教学和应用各种统计方法。 About The Authors 王顺(中南大学),杜新楷,胡传鹏(南京师范大学) 王顺,毕业于中南大学,长期致力于社会学科研究方法和用户体验(User Experience)方面的研究。联系我:shuonwang@gmail.com       杜新楷是五校联合项目Statistical Modeling in Psychology (SMiP) 的在读博士,希望打通高级统计方法与社会科学之间的通道,目前专注于网络模型在社会心理学,尤其是道德领域理论建构和检验的应用与实践。     胡传鹏,南京师范大学心理学院教授,使用贝叶斯方法进行认知建模,关注可重复性与开放科学。Email (hcp4715@hotmail.com; hcp4715@gmail.com)

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La versión en español de JASP ya está en línea!

En un contexto donde los análisis de los datos son importantes, cada vez son más los estudiantes, investigadores y profesionales de distintas disciplinas que utilizan estadísticas. En los países de habla hispana se convierte en una limitación utilizar programas estadísticos sólo en inglés. Por ello, estamos felices de que JASP 0.15 ahora también esté disponible en Español, y esperamos que…

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Introducing JASP 0.16 – Predict with ML Models, Neural Networks, New Techniques for Meta-Analysis, and More.

We are happy to announce that JASP 0.16 has been released and is now available on our download page. JASP 0.16 contains the following new features and improvements: The Meta-Analysis module now includes popular adjustment techniques for publication bias and small study effects: (1) PET-PEESE and (2) WAAP-WLS. Another addition to the Meta-Analysis module is Prediction Model Performance. It is…

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