Minimize the Use of Minimization with Unequal Allocation

Minimization as an alternative to randomization is gaining popularity for small clinical trials. In response to critics' questions about the proper analysis of such a trial, proponents have argued that a rerandomization approach, akin to a permutation test with conventional randomization, can be used. However, they add that this computationally intensive approach is not necessary because its results are very similar to those of a t-test or test of proportions unless the sample size is very small. We show that minimization applied with unequal allocation causes problems that challenge this conventional wisdom.