[R] Clustered data with Design package--bootcov() vs. robcov()
jjharden at gmail.com
Sat May 23 12:35:08 CEST 2009
Another question related to bootcov():
A reviewer is concerned with the fact that bootstrapping the standard errors
does not give the same answers each time. What is a good way to address this
concern? Could I bootstrap, say, 100 times and report the mean standard
error of those 100 estimates? I am already doing 1,000 replications in the
bootstrap, but of course the answer is still slightly different each time.
Frank E Harrell Jr wrote:
> robcov does not use bootstrapping. It uses the cluster sandwich
> (Huber-White) variance-covariance estimator for which there are
> references in the help file (see especially Lin).
> Both robcov and bootcov work best when there is a large number of small
> clusters. If the clusters are somewhat large and greatly vary in size,
> expect to be in trouble and consider a full modeling approach
> (generalized least squares, mixed models, etc.).
> One advantage of robcov is that you get the same result every time,
> unlike bootstrapping. But even in the case of cluster sizes of one, the
> sandwich estimator can be inefficient (see the Gould paper) or can
> result in the "right" estimates of the "wrong" quantity (see a paper by
> Friedman in American Statistician).
>> Thank you.
> Frank E Harrell Jr Professor and Chair School of Medicine
> Department of Biostatistics Vanderbilt University
> R-help at r-project.org mailing list
> PLEASE do read the posting guide
> and provide commented, minimal, self-contained, reproducible code.
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