APPLIED BAYESIAN MODELING
ICPSR SUMMER PROGRAM, JULY 21-23, 2025



Welcome to the website for my workshop Applied Bayesian Models for Social Scientists: From Theory to Estimation and Inference in the 2025 ICPSR Summer Program. This page contains course materials, a variety of information on how to fit and present Bayesian models using Stan and R. Please email me if you have any questions about the material on this page or if you discover any errors. Additional materials for participants will be distributed during the workshop via Canvas. Instructions on how to prepare and what to install will be sent to all participants before the first day of the workshop.

Workshop materials

Installing R, RStudio, and Stan

  1. Install the most recent version of R from the CRAN website.
  2. Download and install the most recent version of RStudio.
  3. We've set time aside to go over installing Stan during the workshop, since it will likely require a few individual adjustments depending on your computer's operating system.

Lab tutorials

The following tutorials (available on Canvas) accompany the labs offered during the workshop:
  1. Installing software
  2. First steps in R
  3. Using Stan via rstanarm
  4. Using Stan via brms
  5. A closer look at convergence
  6. Using MCMC output for postestimation
  7. Writing customized models in Stan via RStan
  8. Writing customized models in Stan via CmdStanR
  9. Constructing and processing multilevel data
  10. Communicating results from Bayesian analysis

R package: BayesPostEst

To facilitate using the methods from this workshop, I provide an R package (jointly authored with Shana Scogin, Andy Beger, and Rob Williams) to generate and plot postestimation quantities after estimating Bayesian regression models using MCMC. Quantities of interest include predicted probabilities and changes in probabilities in generalized linear models and analyses of model fit using ROC curves and precision-recall curves. The package also contains two functions to create publication-ready tables summarizing model results with an assessment of substantively meaningful effect sizes.

Questions? E-mail me.