22 March 2019
Bayesian Structural Equation Modelling
During this course students will be introduced to philosophical underpinnings of Bayesian statistics and will learn how to fit regression, mediation, CFA, and longitudinal growth models in the Bayesian framework. Students will learn the steps in conducting Bayesian analyses and will be able to understand articles that examine and apply Bayesian SEM. The course is highly interactive, and the afternoons will be dedicated to implementing and practicing the material using the participant's software of choice (Mplus or R in tandem with JAGS or stan). We highly recommend bringing your own data for Day 5 of the course; however, the instructors will have example data sets for participants who do not have their own data.
Prof. Dr. Rens van de Schoot works as a professor at Utrecht University in the Netherlands and as extra-ordinary professor North-West University in South-Africa. He is a member of the Young Academy of The Royal Netherlands Academy of Arts and Sciences (KN
Participants will find the course useful if they
- Are interested in using Bayesian statistics in their own work.
- Encounter convergence issues using classical methods.
- Have small samples and/or access to prior information from previous studies.
- Wish to understand new methodological developments that make use of Bayesian statistics and/or Markov Chain Monte Carlo (MCMC).
Participants should have knowledge of regression analysis and basic SEM. No previous knowledge of Bayesian analysis is assumed. Participants should have a good grasp of the software package they plan to use (R or Mplus).
By the end of the course participants will
- Know the differences between 'classical' and Bayesian statistics, and when to use to Bayesian analyses instead of classical statistics.
- Know how to apply Bayesian SEM to analyze their own data.
- Know how to apply the WAMBS-checklist (When to worry and how to Avoid the Misuse of Bayesian Statistics).
- Critically evaluate applications of Bayesian methods in scientific studies.
PhD students have the opportunity to receive European Credit Transfer System (ECTS) points thanks to our cooperation with the Cologne Graduate School in Management, Economics and Social Sciences of the University of Cologne. You will be charged an administration fee of EUR 50,00 (3 ECTS points).
EUR 300: Student/PhD student rate.
EUR 450: Academic/non-profit/public sector rate.
The rates include the tuition fee, course materials, access to library and IT facilities, coffee/tea breaks and social activities.