6 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…
Principal Components Decomposition of Fraction of Variance Explained in High Dimensional Linear Models with Strong Correlation
Man Luo, Chun Chieh Fan, David Azriel +1
The fraction of variance explained (FVE) in a linear model quantifies the extent to which predictors account for outcome variability. In high-dimensional settings, where traditiona…
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…
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,…
Consistency of heritability estimation from summary statistics in high-dimensional linear models
David Azriel, Samuel Davenport, Armin Schwartzman
In Genome-Wide Association Studies (GWAS), heritability is defined as the fraction of variance of an outcome explained by a large number of genetic predictors in a high-dimensional…
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…