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st: Cluster Randomised Trials


From   Lists <scmoore.lists@googlemail.com>
To   statalist@hsphsun2.harvard.edu
Subject   st: Cluster Randomised Trials
Date   Wed, 01 Jul 2009 10:08:10 +0100


Dear Statalist

We have areas in which interventions are deployed. Areas are in matched pairs, matched on certain demographic and other characteristics that might determine effect sizes. The intervention is randomised in each pair. We also have regions and would like to cluster on region as there are large differences in certain demographics across regions. To measure the effect of the intervention we survey individuals in each area before and after the intervention. Due to the location of the survey we anticipate differences in sample sizes for each survey. I’ve been looking through Hayes and Moulton’s recently published book Cluster Randomised Trials, which is great and very Stata friendly. However, I cannot see an easy way to incorporate the levels of information we have into the available models. So far I have the option of using t-tests or xtmixed on outcome surveys, or even manually computing some metric of change. Presumably, though, this is not a particularly unusual problem and so wondered whether anyone here on Statalist might be able to point me towards suitable resources or even an example? There are other issues with the CRT studies that are seemingly avoided in the literature – that of contamination. If outcome measures are both sensitive to both the intervention’s effect but also tempered by individual characteristics, and one has a metric describing the levels of contamination across treatment arms it would seem reasonable to adjust accordingly. Though I fear this would be a step too far at the moment.

Thanks in advance

Simon

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