Evaluation of the type I error rate when using parametric bootstrap analysis of a cluster randomized controlled trial with binary outcomes and a small number of clusters

•The type I error rate is inflated under scenarios of a small number of clusters per treatment in a cluster randomized trials when using parametric bootstrap.•When analyzing cluster randomized trials, the pbkrtest package is limited in performance as it resamples the observations ignoring clusters.•We want to highlight that while the well-known nesting/degrees of freedom issue undermines p-values when k <= 20, we show here that small number of clusters and small ICC inflate type I error rates, setting the nesting/df issue aside.