Bayesian Analysis in Stata

Instructor(s):

  • Gustavo Sanchez, StataCorp

This workshop will be offered in an online video format.

This three-day ICPSR summer workshop will introduce basic concepts relevant to Bayesian analysis and will focus on how to use this approach for regression estimation in Stata.

In recent years, researchers across disciplines have become increasingly interested in Bayesian analysis. This is not surprising because researchers often have some prior knowledge about parameters of interest, and this can be incorporated when using Bayesian estimation. This approach also provides a more natural interpretation of the results in terms of probabilities. Another attractive characteristic of Bayesian regression is that it offers a common theoretical framework for a wide variety of models.

The workshop will consist of a mixture of classroom discussion and interactive demonstrations using Stata software. We will start with a brief overview where we will highlight the components of Bayesian analysis as well as the advantages and disadvantages. We will then discuss theoretical aspects associated with Bayesian statistics and inference and the Markov chain Monte Carlo (MCMC) simulation-based method of estimating posterior distributions. Throughout the course, we will work examples that illustrate Bayesian analysis concepts, and we will demonstrate how to perform these analyses using Stata. Through these examples, we will learn how to perform Bayesian estimation, check for convergence of the MCMC simulation, make inferences, and obtain Bayesian predictions for forecasting and goodness of fit.

Registration Fee: Members = $1,400; Non-members = $2,700

Course Sections

Section 1

Location: Online -- Video format,

Date(s): July 8 - July 10

Time: 9:00 AM - 5:00 PM

Instructor(s):

  • Gustavo Sanchez, StataCorp

Syllabus: