References

Texts for Your Shelf

The following are three texts I have recommended in the past to folks who are interested in doing Bayesian data analysis. They can be seen as introduction, intermediate, and advanced respectively.

Kruschke, J. (2014) Doing Bayesian Data Analysis. A very introductory text, but might be good for those not too confident in statistics generally speaking. And who doesn’t like puppies? 2nd Edition.

McElreath, R. (2020). Statistical Rethinking. A great modeling book in general, by one who has contributed a lot to helping others learn Stan and Bayesian analysis. 2nd Edition.

Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., and Rubin, D. B. (2013). Bayesian Data Analysis. 3rd Edition.

Stan Specific Resources

Main website

Stan Users Group

Stan Best Practices

Example Models

More resources here

Works Cited/Used

Carpenter, Bob, Andrew Gelman, Matthew D Hoffman, Daniel Lee, Ben Goodrich, Michael Betancourt, Marcus Brubaker, Jiqiang Guo, Peter Li, and Allen Riddell. 2017. “Stan: A Probabilistic Programming Language.” Journal of Statistical Software 76 (1).
Gelman, Andrew, John B. Carlin, Hal S. Stern, David B. Dunson, Aki Vehtari, and Donald B. Rubin. 2013. Bayesian Data Analysis. 3rd ed. http://www.stat.columbia.edu/~gelman/book/.
Gelman, Andrew, and Jennifer Hill. 2006. Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press.
Gelman, Andrew, Jessica Hwang, and Aki Vehtari. 2014. “Understanding Predictive Information Criteria for Bayesian Models.” Statistics and Computing 24 (6): 997–1016.
Gelman, Andrew, and Iain Pardoe. 2006. “Bayesian Measures of Explained Variance and Pooling in Multilevel (Hierarchical) Models.” Technometrics 48 (2): 241–51.
Gill, Jeff. 2008. Bayesian Methods : A Social and Behavioral Sciences Approach. Second. Boca Raton: Chapman & Hall/CRC.
Jackman, Simon. 2009. Bayesian Analysis for the Social Sciences. Chichester, UK: Wiley.
Kruschke, John. 2014. Doing Bayesian Data Analysis: A Tutorial with r, JAGS, and Stan. Academic Press.
Lunn, David, Chris Jackson, Nicky Best, Andrew Thomas, and David Spiegelhalter. 2012. The BUGS Book: A Practical Introduction to Bayesian Analysis. Boca Raton, FL: Chapman; Hall/CRC.
Lynch, Scott M. 2007. Introduction to Applied Bayesian Statistics and Estimation for Social Scientists. New York: Springer.
McElreath, Richard. 2020. Statistical Rethinking: A Bayesian Course with Examples in r and Stan. Chapman; Hall/CRC.
McGrayne, Sharon Bertsch. 2012. The Theory That Would Not Die: How Bayes’ Rule Cracked the Enigma Code, Hunted down Russian Submarines, and Emerged Triumphant from Two Centuries of Controversy. Reprint. New Haven Conn.: Yale University Press.
Vehtari, Aki, and Andrew Gelman. 2014. “WAIC and Cross-Validation in Stan.”
Vehtari, Aki, Andrew Gelman, and Jonah Gabry. 2017. “Practical Bayesian Model Evaluation Using Leave-One-Out Cross-Validation and WAIC.” Statistics and Computing 27 (5): 1413–32.
Vehtari, Aki, Daniel Simpson, Andrew Gelman, Yuling Yao, and Jonah Gabry. 2015. “Pareto Smoothed Importance Sampling.” arXiv Preprint arXiv:1507.02646.