32 citations · 63 across the 9 of their papers we have counts for
7 papers · 1 filter
Prognostic Covariate Adjustment for Logistic Regression in Randomized Controlled Trials
Yunfan Li, Arman Sabbaghi, Jonathan R. Walsh +1
Randomized controlled trials (RCTs) with binary primary endpoints introduce novel challenges for inferring the causal effects of treatments. The most significant challenge is non-c…
Bayesian Prognostic Covariate Adjustment With Additive Mixture Priors
Alyssa M. Vanderbeek, Arman Sabbaghi, Jon R. Walsh +1
Effective and rapid decision-making from randomized controlled trials (RCTs) requires unbiased and precise treatment effect inferences. Two strategies to address this requirement a…
A Weighted Prognostic Covariate Adjustment Method for Efficient and Powerful Treatment Effect Inferences in Randomized Controlled Trials
Alyssa M. Vanderbeek, Anna A. Vidovszky, Jessica L. Ross +8
A crucial task for a randomized controlled trial (RCT) is to specify a statistical method that can yield an efficient estimator and powerful test for the treatment effect. A novel…
Degree of Interference: A General Framework For Causal Inference Under Interference
Yuki Ohnishi, Bikram Karmakar, Arman Sabbaghi
One core assumption typically adopted for valid causal inference is that of no interference between experimental units, i.e., the outcome of an experimental unit is unaffected by t…
Distributed Design for Causal Inferences on Big Observational Data
Yumin Zhang, Arman Sabbaghi
A fundamental issue in causal inference for Big Observational Data is confounding due to covariate imbalances between treatment groups. This can be addressed by designing the data…
A Bayesian Analysis of Two-Stage Randomized Experiments in the Presence of Interference, Treatment Nonadherence, and Missing Outcomes
Yuki Ohnishi, Arman Sabbaghi
Three critical issues for causal inference that often occur in modern, complicated experiments are interference, treatment nonadherence, and missing outcomes. A great deal of resea…
Comments on the Neyman-Fisher Controversy and Its Consequences
Arman Sabbaghi, Donald B. Rubin
The Neyman-Fisher controversy considered here originated with the 1935 presentation of Jerzy Neyman's Statistical Problems in Agricultural Experimentation to the Royal Statistical…