title: A hybrid approach to achieving both marginal and conditional balances for stratification variables in sequential clinical trials.
abstract: Various methods exist in the literature for achieving marginal balance for baseline stratification variables in sequential clinical trials. One major limitation with balancing on the margins of the stratification variables is that there is an efficiency loss when the primary analysis is stratified. To preserve the efficiency of a stratified analysis one recently proposed approach balances on the crossing of the stratification variables included in the analysis, which achieves conditional balance for the variables. A hybrid approach to achieving both marginal and conditional balances in sequential clinical trials is proposed, which is applicable to both continuous and categorical stratification variables. Numerical results based on extensive simulation studies and a real dataset show that the proposed approach outperforms the existing ones and is particularly useful when both additive and stratified models are planned for a trial.
authors.affiliation: Department of Statistics, University of Wisconsin - Madison, Madison, WI, USA.
authors.forename: Yunzhi
authors.initials: Y
authors.lastname: Lin
authors.forename: Zheng
authors.initials: Z
authors.lastname: Su
mesh_terms: D015987:Effect Modifier, Epidemiologic; D006801:Humans; D015233:Models, Statistical; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data*
keywords: clinical trial; imbalance; minimization; randomization; stratification variable