- Cluster randomization trials are experiments where intact social units like medical practices, communities, or hospitals are randomly assigned to intervention groups rather than independent individuals. This is done when the intervention is naturally applied at a cluster level or to avoid treatment contamination between groups. - Challenges of cluster randomization trials include having a unit of randomization that differs from the unit of analysis and reduced power due to intracluster correlation. Statistical methods like mixed models that account for clustering are needed to properly analyze results. - Proper sample size calculations are also more complex in cluster randomization trials due to the need to adjust for the intracluster correlation coefficient and design effect. Ensuring enough clusters are enrolled is important to maintain adequate power