Re: st: cluster() or svy? (analysis of cluster-randomized trials)

[Jeph Herrin <junk@spandrel.net>]

I think there are good reasons to avoid both. You don't
say what kinds of analyses you have, but see

 ssc describe cltest

for some tools and a reference for analyzing cluster
randomized outcomes using adjustments to the standard
chi-2 and t-tests. (As author I'll note that the CIs
for the group means reported for the t-test are correct
as documented but nonetheless ad hoc; this doesn't effect
either the p-value or the CI for the difference in means.)

Another preferred option is to use panel methods such
as -xtmixed- with the clusters specified as panels. Even
if you don't have covariates (and in an RCT you will need
to make a case for including them), these are often
preferred.

More detail on your design might produce more detailed
answers.

Hope this helps,
Jeph


Michael I. Lichter wrote:
> Hello, friends. I have a question about the analysis of data from 
> cluster-randomized trials (CRTs). CRTs are experiments where subjects 
> are randomly assigned to conditions (control, treatment) based on their 
> group membership rather than being assigned individually as is usually 
> the case in randomized controlled trials. In my study, the clusters are 
> medical practices, so when a medical practice is assigned to a 
> condition, all of the eligible patients therein are also assigned to the 
> condition. CRTs should be analyzed using methods that take account of 
> the clustering in the study design, of course.
>
> My question is this: For CRTs, is there any statistical reason for 
> preferring the cluster() option on estimation commands (e.g., regress, 
> logit) over the survey commands, or vice-versa? I've used both and the 
> results are similar, but the survey commands estimate larger standard 
> errors. If the answer is that they're both equally appropriate but 
> produce different results because they use somewhat different methods of 
> estimation, that's fine.
>
> Thanks.
>
> Michael
>
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