Using Bayesian Variable Selection to Analyze Regular Resolution IV Two-level Fractional Factorial Designs

Regular two‐level fractional factorial designs have complete aliasing in which the associated columns of multiple effects are identical. In this article, we show how Bayesian variable selection can be used to analyze experiments that use such designs. Bayesian variable selection naturally incorporates heredity in addition to sparsity and hierarchy. This prior information is used to identify the most likely combinations of active terms. The method is demonstrated on simulated and real experiments.