Clinical trials : journal of the Society for Clinical Trials
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We describe different forms of clustering that may occur in individually randomized trials, where the observed outcomes for different individuals cannot be regarded as independent. We propose random effects models to allow for such clustering, across a range of contexts and trial designs, and investigate their effect on estimation and interpretation of the treatment effect. ⋯ Clustering is an important issue in many individually randomized trials. Ignoring it can lead to underestimates of the uncertainty and too extreme P-values. Even when there is little apparent heterogeneity across clusters, it can still have a large impact on the estimation and interpretation of the treatment effect.