Table 1.

Description of Competing Randomization Procedures for Cluster Designs

Randomization Procedure	Description	Advantages	Disadvantages
Simple Randomization	Unrestricted technique, based on single sequence random assignment. All allocations of units randomized are possible.	Simple and easy to implement. Balances covariates with large sample sizes.	Subjects enrolled may not have balance on covariates when the sample size is moderate or small.
Stratified Randomization	Restricted technique: Create a stratum for each combination of covariates being considered. Units are then randomly assigned to treatment arms within each stratum.	Reduces imbalance between treatment groups on important covariates. Able to control and balance covariates of importance.	Limited number of factors can be stratified on, and need to be willing to categorize continuous variables. Number of strata needed increases rapidly as the number of covariates increases.
Matching	Restricted technique: Select from a smaller set of all possible allocations, those fulfilling certain restrictions (i.e. meet the matching criteria), and then randomly allocate to the treatment arms within each match.	Reduces imbalance between treatment groups on important covariates. Able to control and balance covariates of importance.	Need to identify pairs of clusters that are well-matched on all of the risk factors, which is often not feasible, especially when subsets of people are enrolled in each cluster post-randomization. Need to set suitable balance criteria.
Covariate Constrained Randomization	Restricted technique: Find the number of allocations meeting a set of balancing criteria for the covariates of interest. Ensure that overly constrained designs do not exist (e.g. same clusters always appearing in same group) – otherwise need to adjust balance criteria. Randomly select one allocation for the study.	Can attain balance (or near balance) on covariates related to outcome resulting in a gain in efficiency. Do not need to categorize covariates.	Need to set suitable balance criteria. If balance criteria are too restricted, it could result in biased or invalid design. Performed at the start of trial, so infeasible when need to add more clusters.
Minimal Sufficient Balance [29]	Restricted technique: Distribution of covariates between treatment arms assessed using imbalance tests, and depending on results units are assigned treatment based on biased coin or simple random assignment	Prevents serious imbalance on important covariates, while maintaining randomness of treatment allocation. Do not need to categorize covariates.	Expected that units are being randomized sequentially. Could be deterministic. Need to set suitable balance criteria.
Minimization [10]	Restricted technique: Sequentially assign units to treatment groups taking into account the balance on covariates and previous randomization assignments.	Maintains balance among several covariates, while minimizing imbalance in the distribution of the treatment across whole trial and each stratification variable.	Expectation is that units being randomized are available sequentially, which is usually not the case in a cluster-randomized trial. Could have imbalance in specific strata. Criticized for being too deterministic.
Dynamic Randomization [12]	Restricted technique: For each level of a stratification hierarchy, a balance criteria is set, to keep imbalances from exceeding these limits. If imbalance is within limits for all levels, unit is randomly assigned, otherwise allocation is forced at stratification level where limits exceeded to reduce imbalance.	Maintains balance on treatment assignments across the whole trial and within each strata. Most useful in unblinded trials.	Need a centrally administered trial. Expected that units are being randomized sequentially.
Outcome Adaptive Randomization [30]	Restricted technique: Class of methods including those proposed by Bather, [31] Thompson, [32] Zelen, [33] Sobel and Weiss, [34] and Berry and Fristedt, [35] in which treatment assignment is dependent on response of previous individuals.	Objective is to maximize the number of overall successes, maximize effective treatment.	Expected that units are being randomized sequentially. Need real time reporting of outcomes that can be measured shortly after treatment initiation, (e.g. pain relief for a treatment).