Clustered data with Design package--bootcov() vs. robcov()

Hi,

I am trying to figure out exactly what the bootcov() function in the Design
package is doing within the context of clustered data. From reading the
documentation/source code it appears that using bootcov() with the cluster
argument constructs standard errors by resampling whole clusters of
observations with replacement rather than resampling individual
observations. Is that right, and is there any more detailed documentation on
the math behind this? Also, what is the difference between these two
functions:

bootcov(my.model, cluster.id)
robcov(my.model, cluster.id)

Thank you.

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