When should matching be used in the design of cluster randomised trials?

Abstract

For cluster randomised trials (CRT) with a small number of clusters, the matched-pair (MP) design, where clusters are paired before randomising one to each trial arm, is often recommended to minimise imbalance on known prognostic factors, add face-validity to the study and increase efficiency, provided the analysis recognises the matching. Little evidence exists to guide decisions on when to use matching. We used simulation to compare the efficiency of the MP design with the stratified and simple designs, based on the mean confidence interval width of the estimated intervention effect. Matched and unmatched analyses were used for the MP design; a stratified analysis was used for the stratified design; and analyses without and with post-stratification adjustment for factors that would otherwise have been used for restricted allocation were used for the simple design. Results showed the MP design was generally the most efficient for CRTs with 10 or more pairs when the correlation between cluster-level outcomes within pairs (matching correlation) was moderate to strong (0.3 to 0.5). There was little gain in efficiency for the matched-pair or stratified designs compared to simple randomisation when the matching correlation was weak (0.05 to 0.1). For trials with 4 pairs of clusters, the simple and stratified designs were more efficient than the MP design because greater degrees of freedom were available for the analysis, although an unmatched analysis of the MP design recovered precision for weak matching correlations. Practical guidance on choosing between the matched-pair, stratified and simple designs is provided.