%0 Journal Article
%T Planning a cluster randomized trial with unequal cluster sizes: practical issues involving continuous outcomes
%A Lydia Guittet
%A Philippe Ravaud
%A Bruno Giraudeau
%J BMC Medical Research Methodology
%D 2006
%I BioMed Central
%R 10.1186/1471-2288-6-17
%X We performed simulations to study the impact of an imbalance in cluster size on power. We determined by simulations to which extent four methods proposed to adapt the sample size calculations to a pre-specified imbalance in cluster size could lead to adequately powered trials.We showed that an imbalance in cluster size can be of high influence on the power in the case of severe imbalance, particularly if the number of clusters is low and/or the intraclass correlation coefficient is high. In the case of a severe imbalance, our simulations confirmed that the minimum variance weights correction of the variation inflaction factor (VIF) used in the sample size calculations has the best properties.Publication of cluster sizes is important to assess the real power of the trial which was conducted and to help designing future trials. We derived an adaptation of the VIF from the minimum variance weights correction to be used in case the imbalance can be a priori formulated such as "a proportion (¦Ã) of clusters actually recruit a proportion (¦Ó) of subjects to be included (¦Ã ¡Ü ¦Ó)".A cluster randomized trial involves randomizing social units or clusters of individuals rather than the individuals themselves. This design, which is increasingly being used for evaluating healthcare, screening and educational interventions presents specific constraints that must be considered during planning and analysis [1,2]. Indeed, the responses of individuals within a cluster tend to be more similar than those of individuals of different clusters, and we thus define the clustering effect as 1 + (m - 1)¦Ñ, where m is the average number of subjects per cluster and ¦Ñ the intraclass correlation coefficient (ICC). This clustering effect is used during the planning of cluster randomized trials as an inflation factor to increase the sample size required by an individual randomization trial. However, such an approach does not take into account variations in cluster size, which might differ greatly. Inde
%U http://www.biomedcentral.com/1471-2288/6/17