Materials for Bayesian data analysis practice with RStan (In Russian)
1.1 Introduction to Stan probabilistic language
1.2 How to estimate parameters with RStan (examples: normal and binomial cases)
1.3 How to check convergence of chains and adequacy of posterior sampling
2.1 Bayesian linear regression
3.1 Bayesian hierarchical models
3.2 Bayesian mixed logistic regression: practice with the real data
4.1 How to define hypotheses as probabilistic models. Reading: Etz, A., Haaf, J. M., Rouder, J. N., Vandekerckhove, J. (2018). Bayesian inference and testing any hypothesis you can specify. Advances in Methods and Practices in Psychological Science, 1(2), 281-295. https://psyarxiv.com/wmf3r/
4.2 Bridgesampling and computing of Bayes-factor
4.3 Testing hypotheses of the real experiment
Some of the materials are adapted from or inspired by the Summer School of Statistical Methods for Linguistics and Psychology (Potsdam, 2017). Materials from this school can be found here: https://vasishth.github.io/SMLP2017/.