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st: Robust variances

From   Constantine Daskalakis <[email protected]>
To   [email protected]
Subject   st: Robust variances
Date   Fri, 23 May 2003 17:22:01 -0400

At 04:48 PM 5/23/03, Mark Schaffer wrote:
Hi everybody.  With respect to clustering,

Personally, I think this problem is VERY easy to stumble into [decoded =
I've done it myself] and could do with much more highlighting in the
manuals, and in the on-line help and error messages.

I am confused.

Consider the simplest case where I compute a robust variance from all the data (ie, a single cluster). Are you saying that I get information equivalent to an observation of 1? That is certainly not the case. Only if the actual correlation is 1, I will get an "effective" N of 1. If the actual correlation is 0, I will get an "effective" N similar to my original observations. In this simple case, are you then saying that the robust variance is nonsense? The Liang and Zeger GEE approach does exactly that and it's been shown to be consistent in lots of situations, so your point must be different.

Maybe you're arguing that, with a single cluster, the robust variance is fine, but when you sum across clusters, then you have to have a "large number" of clusters?

Any comments/direction from the good Stata people on this?


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Constantine Daskalakis, ScD
Assistant Professor,
Biostatistics Section, Thomas Jefferson University,
125 S. 9th St. #402, Philadelphia, PA 19107
Tel: 215-955-5695
Fax: 215-503-3804
Email: [email protected]

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