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03/24/2023
Towards Outcome-Driven Patient Subgroups: A Machine Learning Analysis Across Six Depression Treatment Studies
Major depressive disorder (MDD) is a heterogeneous condition; multiple u...
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12/04/2022
The Optimality of Blocking Designs in Experiments with General Response
We consider the problem of evaluating designs for a two-arm randomized e...
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09/01/2022
The Role of Pairwise Matching in Experimental Design for an Incidence Outcome
We consider the problem of evaluating designs for a two-arm randomized e...
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12/06/2020
Better Experimental Design by Hybridizing Binary Matching with Imbalance Optimization
We present a new experimental design procedure that divides a set of exp...
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10/12/2020
A Matching Procedure for Sequential Experiments that Iteratively Learns which Covariates Improve Power
We propose a dynamic allocation procedure that increases power and effic...
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08/13/2020
Improving the Power of the Randomization Test
We consider the problem of evaluating designs for a two-arm randomized e...
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05/08/2019
Optimal Rerandomization via a Criterion that Provides Insurance Against Failed Experiments
We present an optimized rerandomization design procedure for a non-seque...
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10/19/2018
Harmonizing Fully Optimal Designs with Classic Randomization in Fixed Trial Experiments
There is a movement in design of experiments away from the classic rando...
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12/08/2013
bartMachine: Machine Learning with Bayesian Additive Regression Trees
We present a new package in R implementing Bayesian additive regression ...
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06/03/2013