2 citations · 5 across the 14 of their papers we have counts for
5 papers · 1 filter
An Efficient Framework for Robust Sample Size Determination
Luke Hagar, Andrew J. Martin
In many settings, robust data analysis involves computational methods for uncertainty quantification and statistical inference. To design frequentist studies that leverage robust a…
Bayesian Design of Experiments in the Presence of Nuisance Parameters
Shirin Golchi, Luke Hagar
Design of experiments has traditionally relied on the frequentist hypothesis testing framework where the optimal size of the experiment is specified as the minimum sample size that…
An Efficient Approach to Design Bayesian Platform Trials
Luke Hagar, Lara Maleyeff, Shirin Golchi +1
Platform trials evaluate multiple experimental treatments against a common control group (and/or against each other), which often reduces the trial duration and sample size. Bayesi…
Classifying group actions on hyperbolic spaces
D. Osin, K. Oyakawa, A. Rapinchuk
For a given group , it is natural to ask whether one can classify all isometric -actions on Gromov hyperbolic spaces. We propose a formalization of this problem utilizing the…
Design of Bayesian Clinical Trials with Clustered Data
Luke Hagar, Shirin Golchi
In the design of clinical trials, it is essential to assess the design operating characteristics (e.g., power and the type I error rate). Common practice for the evaluation of oper…