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Beyond null hypo testing: (non-)Bayesian evaluation of informative hypotheses

Semester

Semester 1, 2025-2026

Type of course

Methodological and Practical Courses

Date

October 29, 2025

Location

Utrecht University

Duration

1 day

Maximum number of participants

40

ECTS

0.5 EC will be appointed for participation in the complete course

Staff

Rebecca Kuiper (UU)

Content

Because of the ongoing replication crisis, researchers increasingly recognize the need for alternatives to traditional null-hypothesis testing. This workshop addresses such methods by introducing participants to:

  1. Theory-based, informative hypotheses
  2. Model selection methods for evaluating such hypotheses, specifically the Bayes factor and the AIC-type information criterion GORIC(A).

Instead of coming to a dichotomous decision, one can now quantity the (relative) support for the hypothesis of interest.

The workshop emphasizes concepts and practical examples rather than mathematical formulas. During the lecture, participants will engage in “hands-on” sessions, and we end with a lab meeting. We will make use of the R packages bain and restriktor (particularly the goric function). For those who prefer not to work with R, equivalent lab materials will also be provided in JASP.

Learning goals

Learn to set up, apply, and interpret informative hypothesis evaluation (using Bayesian model selection and GORIC(A)).

Course material

The course materials can be downloaded from https://github.com/rebeccakuiper/Tutorials/tree/main/KLI%20course.

This will be up to date just before the start of the course.

Preparation

You can prepare by installing - before the start of the course - the software you like to use:

- Install R, RStudio, and the R packages bain and restriktor; 

  • R can be downloadedhere.
  • RStudio can be downloadedhere.

If you need to refresh your R skills, do the R hands-on mini course (‘R hands-on mini course.pdf’) available via the link above. 

- If you prefer not to work with R, you can use JASP: https://jasp-stats.org/.

Time schedule

09.45-10.00       Welcome with tea/coffee 

10.00-12.00       Lecture and hands-on: Introduction to informative hypotheses and their evaluation

12.00-1.00         Lunch

1.00-2.15           Lecture and hands-on continued

2.15-2.30           Tea/coffee break

2.30-5.00           Lab meeting: work on exercises and possibly, if available, apply the learned methods on your own data