activity
20072026
most citedSelect sets: Rank and file

15 citations · 38 across the 14 of their papers we have counts for

collaborators

17 papers

stat.ME2026

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…

stat.ME2025

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…

stat.ME2024

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…

math.ST2022

The Optimality of Blocking Designs in Equally and Unequally Allocated Randomized Experiments with General Response

David Azriel, Abba M. Krieger, Adam Kapelner

We consider the performance of the difference-in-means estimator in a two-arm randomized experiment under common experimental endpoints such as continuous (regression), incidence,…

stat.ME2022

The Role of Pairwise Matching in Experimental Design for an Incidence Outcome

Adam Kapelner, Abba M. Krieger, David Azriel

We consider the problem of evaluating designs for a two-arm randomized experiment with an incidence (binary) outcome under a nonparametric general response model. Our two main resu…

stat.ME2021★ 5 cited

Optimal multiple testing and design in clinical trials

Ruth Heller, Abba Krieger, Saharon Rosset

A central goal in designing clinical trials is to find the test that maximizes power (or equivalently minimizes required sample size) for finding a false null hypothesis subject to…