As randomization methods use more information in more complex ways to assign patients to
treatments, analysis of the resulting data becomes challenging. The treatment assignment …

Linear regression is arguably the most fundamental statistical model; however, the validity of
its use in randomized clinical trials, despite being common practice, has never been crystal …

In clinical trials, several covariate-adaptive designs have been proposed to balance
treatment arms with respect to key covariates. Although some argue that conventional …

Covariate-adaptive randomization (CAR) is widely used in clinical trials to balance treatment
allocation over covariates. Over the past decade, significant progress has been made on the …

Randomization tests (sometimes referred to as “re-randomization” tests) are used in clinical
trials, either as an assumption-free confirmation of parametric analyses, or as an …

Often patients may require treatment on multiple occasions. The re-randomisation design
can be used in such multi-episode settings, as it allows patients to be re-enrolled and re …

We demonstrate that clinical trials using response adaptive randomized treatment
assignment rules are subject to substantial bias if there are time trends in unknown …

We provide a theoretical template for the comparison of response-adaptive randomization
procedures for clinical trials. Using a Taylor expansion of the noncentrality parameter of the …

Covariate-adaptive randomisation has a more than 45 years of history of applications in
clinical trials, in order to balance treatment assignments across prognostic factors that may …

Covariate-adaptive randomization is gaining popularity in clinical trials because they enable
the generation of balanced allocations with respect to covariates. Over the past decade …