I need to perform a bootstrap for variance estimation on a GEE model for clustered data that I am analyzing. I understand that I need to use a clustered bootstrap for this, which is pretty much the same thing as the usual nonparametric bootstrap, only the clusters are sampled rather than the individual observations within a cluster. I've read a few articles on this and the articles always assume clusters of equal size. Can the clustered bootstrap be modified for clusters of unequal size? If so, how is this done? In the usual bootstrap, resampling with replacement is performed until the dataset is the same size of the original dataset. How do we perform a cluster bootstrap with unequal sized clusters such that the $i$th bootstrap sample is the same size as the original dataset? I could imagine a situation where the cluster sizes are different such that it might be impossible to obtain datasets of the same size as the original dataset if we sample clusters, stead of elements.
Lastly is there a procedure in SAS or R that will perform the cluster bootstrap?