Power Prior Bayesian Analysis using PROC BGLIMM

Music City Center 

The power prior, a general class of priors that are used in Bayesian analysis, provides a practical and dynamic approach to translate data information into distributional information about the model parameters. The power prior has become a popular method in many disciplines, as it increases model efficiency and prediction accuracy by borrowing information from other data sources. Implementation of the power prior can be difficult using general Bayesian software packages and often relies on programming solutions that are problem-specific, making it hard to generalize. We introduce new features in the BGLIMM procedure that enables you to fit the power prior to many models with the simplest setup.

Bayesian analysis

historical data

information borrowing

power prior

PROC BGLIMM 

Section on Bayesian Statistical Science