Prognostic Covariate Adjustment for Logistic Regression in Randomized Controlled Trials

no code implementations • 29 Feb 2024 • Yunfan Li, Arman Sabbaghi, Jonathan R. Walsh, Charles K. Fisher

We demonstrate that prognostic score adjustment in logistic regression increases the power of the Wald test for the conditional odds ratio under a fixed sample size, or alternatively reduces the necessary sample size to achieve a desired power, compared to the unadjusted analysis.

regression

Bayesian Prognostic Covariate Adjustment With Additive Mixture Priors

no code implementations • 27 Oct 2023 • Alyssa M. Vanderbeek, Arman Sabbaghi, Jon R. Walsh, Charles K. Fisher

We propose a new Bayesian prognostic covariate adjustment methodology, referred to as Bayesian PROCOVA, that combines these two strategies.

Decision Making

A Weighted Prognostic Covariate Adjustment Method for Efficient and Powerful Treatment Effect Inferences in Randomized Controlled Trials

no code implementations • 25 Sep 2023 • Alyssa M. Vanderbeek, Anna A. Vidovszky, Jessica L. Ross, Arman Sabbaghi, Jonathan R. Walsh, Charles K. Fisher, the Critical Path for Alzheimer's Disease, the Alzheimer's Disease Neuroimaging Initiative, the European Prevention of Alzheimer's Disease, Consortium, the Alzheimer's Disease Cooperative Study

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.

regression