Sample size estimation in cluster randomized trials: an evidence-based perspective The evidence-based perspective to sample size estimation determines appropriate trial size by examining its potential impact on the literature. This approach is extended to determine the appropriate size of a planned cluster randomized trial by considering the role of the planned trial on a future meta-analysis (including current literature and the proposed study). A simulation-based algorithm allows consideration of variable cluster sizes and intracluster correlation coefficient values in conjunction with three approaches to sample size estimation, namely the power-based, variance reduction and non-inferiority perspectives. Two examples employing the sample size estimation techniques described are discussed in detail, while appropriate code is provided in the accompanying R package CRTSize.