40 citations · 53 across the 6 of their papers we have counts for
8 papers · 1 filter
On variance of the treatment effect in the treated using inverse probability weighting
Sarah A. Reifeis, Michael G. Hudgens
In the analysis of observational studies, inverse probability weighting (IPW) is commonly used to consistently estimate the average treatment effect (ATE) or the average treatment…
Balanced Policy Evaluation and Learning for Right Censored Data
Owen E. Leete, Nathan Kallus, Michael G. Hudgens +2
Individualized treatment rules can lead to better health outcomes when patients have heterogeneous responses to treatment. Very few individualized treatment rule estimation methods…
Estimands and Inference in Cluster-Randomized Vaccine Trials
Kayla W. Kilpatrick, Michael G. Hudgens, M. Elizabeth Halloran
Cluster-randomized trials are often conducted to assess vaccine effects. Defining estimands of interest before conducting a trial is integral to the alignment between a study's obj…
Inverse Probability Weighted Estimators of Vaccine Effects Accommodating Partial Interference and Censoring
Sujatro Chakladar, Michael G. Hudgens, M. Elizabeth Halloran +3
Estimating population-level effects of a vaccine is challenging because there may be interference, i.e., the outcome of one individual may depend on the vaccination status of anoth…
Exact Power of the Rank-Sum Test for a Continuous Variable
Katie R. Mollan, Ilana M. Trumble, Sarah A. Reifeis +4
Accurate power calculations are essential in small studies containing expensive experimental units or high-stakes exposures. Herein, exact power of the Wilcoxon Mann-Whitney rank-s…
Doubly Robust Estimation in Observational Studies with Partial Interference
Lan Liu, Michael G. Hudgens, Bradley Saul +3
Interference occurs when the treatment (or exposure) of one individual affects the outcomes of others. In some settings it may be reasonable to assume individuals can be partitione…