Program & Events

Abstract Book

The abstract book can be downloaded here.

Workshop Program

Contributions

Posters

If you will present a poster, please make sure it is formatted in dimensions: A0 portrait, 841 mm x 1189 mm. Material for mounting the posters will provided by our team.

Talks

Speaking time is 15 minutes, followes by a 5-minute discussion. If possible, our team will cluster thematically related research talks into topical sessions of 3-4 talks. We recommend a PowerPoint presentation so that the audience can follow your presentation.

Pre-Conference Workshop

The workshop will start on Thursday (June 13th) at 1:30 pm until 6 pm, including breaks.

Introduction to Bayesian Statistics with R and BRMS

Abstract: Bayesian statistics offers a powerful framework for inference and modeling, providing a flexible alternative to traditional frequentist approaches. This workshop aims to provide participants with an introduction to Bayesian statistics, highlighting its fundamental principles and practical applications using the brms package in R.

The workshop will begin with an overview of Bayesian concepts, including the interpretation of priors, likelihoods, and posteriors, as well as the role of Bayesian inference in hypothesis testing and parameter estimation. We will explore the key differences between Bayesian and frequentist statistics, emphasizing the advantages and limitations of each approach.

Following the theoretical foundation, participants will engage in hands-on training using the brms package to fit Bayesian regression models. Starting with simple linear regression models, participants will learn how to specify model formulas, interpret model output, and assess model fit.

Moving beyond linear regression, we will delve into generalized linear models (GLMs), which extend the framework to accommodate non-Gaussian response variables, such as binary or count data.

Throughout the workshop, emphasis will be placed on practical implementation, with interactive exercises and real-world examples to reinforce concepts. By the end of the workshop, participants will have hopefully gained a solid elementary understanding of Bayesian statistics and the ability to apply Bayesian regression modeling techniques using the brms package to their own research questions.

Target Audience: This workshop is suitable for PhD students and researchers with basic familiarity with statistical concepts and R programming. No prior experience with Bayesian statistics or the brms package is required.

Requirements: A computer with R and the BRMS package installed (please make sure to run an example model to ensure it works).

The workshop will be held in english by Dr. Jean-Paul Snijder!

Bio: Dr. Jean-Paul Snijder is currently serving as a postdoctoral researcher at the University of Heidelberg. With a Ph.D. in Cognitive Psychology, Dr. Snijder's research focuses on the precise measurement of cognitive abilities, particularly in the realm of cognitive control. Passionate about advancing psychometric practices, Dr. Snijder is actively involved in developing cutting-edge statistical methodologies, with a particular emphasis on Bayesian statistics. As an avid R user, Dr. Snijder leverages the power of R for data analysis, visualization, and script automation, ensuring high standards of reproducibility, accountability, and shareability in research practices.

jpsnijder.com