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The use of minimization to form comparison groups in educational research

Randomized controlled trials in educational research tend to be small. Small trials can have large, chance, imbalances in important covariates. For studies with sample sizes greater than 50, chance imbalances can be corrected using analysis of covariance; for small trials, however, statistical power is maximized if the trial is balanced and analysis of covariance is used in the analysis. The aim of the present study was to discuss methods of improving covariate balance in trial design and to demonstrate the method of minimization. Using an exemplar of a cluster or class‐randomized trial with 29 classes, we employed minimization to achieve covariate balance. Minimization achieved good balance on four prognostic variables. Many trialists in education use restricted forms of allocation, including pairing or stratified randomization. These approaches have disadvantages. Another approach rarely used in educational research is minimization. Minimization uses a simple arithmetic algorithm to produce balanced groups across a number of important covariates and should be more widely used in educational and psychological research.