Bayesian model averaging

Stata's new bma suite, which performs Bayesian model averaging (BMA), helps address this uncertainty in the context of linear regression. Which predictors are important given the observed data? Which models are more plausible? How do predictors relate to each other across different models? BMA can answer these and more questions. BMA uses the Bayes theorem to aggregate the results across multiple candidate models to account for model uncertainty during inference and prediction in a principled and universal way. In my presentation, I will describe the basics of BMA and demonstrate it with the bma suite. I will also show how BMA can become a useful tool for your regression analysis, Bayesian or not!