2 citations · 7 across the 8 of their papers we have counts for
4 papers · 2 filters
Design of Bayesian A/B Tests Controlling False Discovery Rates and Power
Luke Hagar, Nathaniel T. Stevens
Businesses frequently run online controlled experiments (i.e., A/B tests) to learn about the effect of an intervention on multiple business metrics. To account for multiple hypothe…
Posterior Ramifications of Prior Dependence Structures
Luke Hagar, Nathaniel T. Stevens
Prior elicitation methods for Bayesian analyses transfigure prior information into quantifiable prior distributions. Recently, methods that leverage copulas have been proposed to a…
Bioequivalence Design with Sampling Distribution Segments
Luke Hagar, Nathaniel T. Stevens
In bioequivalence design, power analyses dictate how much data must be collected to detect the absence of clinically important effects. Power is computed as a tail probability in t…
Fast Power Curve Approximation for Posterior Analyses
Luke Hagar, Nathaniel T. Stevens
Bayesian hypothesis tests leverage posterior probabilities, Bayes factors, or credible intervals to inform data-driven decision making. We propose a framework for power curve appro…