Table 1 Allocation techniques for covariate balance in C-RCTs: advantages and limitations
From: Allocation techniques for balance at baseline in cluster randomized trials: a methodological review
Technique | Advantages | Limitations |
|---|---|---|
Simple/Complete randomization | No need for baseline data; most transparent, accepted | Higher risk for imbalance |
Restricted randomization | Â | Â |
Matching | Improves face validity; May balance effectively for many covariates (only if a good match is found) | Loss to follow-up is doubled (pair instead of single loss); challenges with analysis; difficult to estimate/report ICC; reduced degrees of freedom limits power |
Stratification | May be used in combination with other allocation techniques | Can balance for few covariates on its own |
Minimization | Can balance effectively for many covariates | Less transparent, possibly less well-understood by audience; continuous covariates may need to be split into categories; potential for selection bias/predictability |
Covariate-constrained randomization | Balances most effectively for many covariates; limits risk of selection bias | Requires access to baseline data; possibly less well-understood by audience; potential for over-constraint; requires additional statistical support; allocation must occur after recruitment |