408 citations · 695 across the 22 of their papers we have counts for
26 papers
Optimal Designs with Robust Inference for Binary Treatment Effects
David Azriel, Abba M. Krieger, Adam Kapelner
We study randomized experiments with binary outcomes under Neyman's nonparametric model, where covariate measurements are fixed but potential outcomes are random. In this setting w…
Improved Conditional Logistic Regression using Information in Concordant Pairs with Software
Jacob Tennenbaum, Adam Kapelner
We develop an improvement to conditional logistic regression (CLR) in the setting where the parameter of interest is the additive effect of binary treatment effect on log-odds of t…
Predicting Contextual Informativeness for Vocabulary Learning using Deep Learning
Tao Wu, Adam Kapelner
We describe a modern deep learning system that automatically identifies informative contextual examples (\qu{contexts}) for first language vocabulary instruction for high school st…
Block Designs that Provide Optimal Power in the Cochran-Mantel-Haenszel Test
David Azriel, Adam Kapelner, Abba M. Krieger
We consider the asymptotic power performance under local alternatives of the Cochran-Mantel-Haenszel test. Our setting is non-traditional: we investigate randomized experiments tha…
Development and Validation of a Deep-Learning Model for Differential Treatment Benefit Prediction for Adults with Major Depressive Disorder Deployed in the Artificial Intelligence in Depression Medication Enhancement (AIDME) Study
David Benrimoh, Caitrin Armstrong, Joseph Mehltretter +8
INTRODUCTION: The pharmacological treatment of Major Depressive Disorder (MDD) relies on a trial-and-error approach. We introduce an artificial intelligence (AI) model aiming to pe…
The Pairwise Matching Design is Optimal under Extreme Noise and Assignments
David Azriel, Abba M. Krieger, Adam Kapelner
We consider the general performance of the difference-in-means estimator in an equally-allocated two-arm randomized experiment under common experimental endpoints such as continuou…