Document Type


Degree Name



Oregon Health & Science University


Randomization is a key characteristic of clinical trials which makes them the gold standard for determining treatment effectiveness. Response-adaptive randomization is desirable because it allows more patients to receive the best treatment; however, compared to traditional equal randomization, response-adaptive randomization is more likely to allow imbalance in prognostic baseline covariates. We propose a simple yet flexible two-stage randomization for multi-arm trials which marries response-adaptative and covariate-balancing designs. The operating characteristics of the proposed methods were assessed via simulation for a variety of scenarios in which values of treatment success probability and patient response delay time were varied. The newly proposed methods consistently outperformed equal randomization in terms of reducing the proportion of treatment failures for subjects and compared favorably to response-adaptive only randomization while significantly improving the balance of prognostic covariates between treatment arms. The proposed design also compared favorably with a Bayesian approach to response-adaptive covariate-balanced design, providing equal or better power and covariate-balance.




School of Public Health



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