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Randomization is an established process to assign participants to treatment groups to reduce selection bias. Minimization is a method of dynamic or adaptive randomization to minimize the imbalance between treatment groups with respect to the number of participants over the participant’s predefined covariate factors. The algorithms for minimization randomization with equal allocation ratio have been well studied in the literature.
In this presentation, we expand the minimization randomization to a general clinical trial setting with any number of treatment groups and any allocation ratios, using more proposed measures of imbalance by the standard deviation and variance, other than the standard measure by the range. Simulations have been conducted to evaluate the performance of these methods. Furthermore, we will introduce a newly developed R package ‘Minirand’ to implement these algorithms.
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