Yair Haendler (LLF)
Bayesian analysis workflow – advanced course on Bayesian models
Topics:
- Model building.
- Prior predictive checks – whether the priors are plausible with regard to reality.
- Computational faithfulness of the model.
- Testing model sensitivity.
- Posterior predictive checks – whether the model captures the data well.
- Bayes factor analysis to check the evidence for a particular effect.
Requisites: Previous experience fitting and interpreting Bayesian mixed-effects models.