Kim May Lee

Inclusive designs that allow the inclusion of a broader population in randomized controlled trials: An evaluation of randomization ratio and analysis strategy

In most multi-arm randomized controlled trials, all participants need to be eligible to be randomized to all the arms. This means some participants are excluded from participating in multi-arm studies. We propose to relax this by considering a 'differential randomization' approac...

Group sequential designs and a sample size reestimation approach for partially nested trials

Abstract Background Randomized controlled trials are the gold standard for evaluating interventions. For individually randomized trials, clustering can exist in the intervention arm but not the control arm when the intervention is delivered by study personnels and/or in a group s...

Comparison of parametric versus machine-learning multiple imputation in clinical trials with missing continuous outcomes

Abstract Background Flexible machine-learning (ML) models to generate imputations within the Multiple Imputation (MI) framework has recently gained traction, particularly in non-randomised observational settings. For randomised controlled trials (RCTs), it is unclear whether ML a...