Design-Based Bayesian Inference for Causal Effects

• In Event: Advances in Methods for Causal Inference

Brief Overview

This paper develops a design-based mode of Bayesian belief revision that retains important truth-tracking properties, while also permitting nuanced and flexible inferences that improve upon the coarse decision calculus of NHST.

Author

• Thomas Leavitt, Columbia University