Machine learning methods for leveraging baseline covariate information to improve the efficiency of clinical trials

Adaptive pre-specification in randomized trials with and without pair-matching

(2016) Laura B. Balzer et al.   STATISTICS IN MEDICINE

Inverse probability weighting for covariate adjustment in randomized studies

(2013) Changyu Shen et al.   STATISTICS IN MEDICINE

On the covariate-adjusted estimation for an overall treatment difference with data from a randomized comparative clinical trial

(2012) L. Tian et al.   BIOSTATISTICS

Simple, Efficient Estimators of Treatment Effects in Randomized Trials Using Generalized Linear Models to Leverage Baseline Variables

(2010) Michael Rosenblum et al.  

Improving Efficiency of Inferences in Randomized Clinical Trials Using Auxiliary Covariates

(2008) Min Zhang et al.   BIOMETRICS

Empirical Efficiency Maximization: Improved Locally Efficient Covariate Adjustment in Randomized Experiments and Survival Analysis

(2008) Daniel B Rubin et al.  

Covariate adjustment in randomized trials with binary outcomes: Targeted maximum likelihood estimation

(2008) K. L. Moore et al.   STATISTICS IN MEDICINE

Covariate adjustment for two-sample treatment comparisons in randomized clinical trials: A principled yet flexible approach

(2007) Anastasios A. Tsiatis et al.   STATISTICS IN MEDICINE