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SUMMARY:Models for baseline and treatment effects in meta-analysis - Tony 
 Ades\, University of Bristol
DTSTART:20070327T133000Z
DTEND:20070327T143000Z
UID:TALK6348@talks.cam.ac.uk
CONTACT:4904
DESCRIPTION:The widely accepted approach to meta-analysis assumes that the
  trial-specific "baseline" effects are nuisance variables. This is well-su
 ited to inference on the relative treatment effects. However\, for cost-ef
 fectiveness analyses (CEAs) it is necessary to incorporate evidence on abs
 olute effects. The RCT evidence is one possible source of data on absolute
  effects\, and may sometimes be the preferred source. This presents a diff
 iculty: if the trial baselines are nuisance parameters they cannot be used
  to inform a CEA analysis. But if we put a model on the baselines to feed 
 into the CEA\, then this changes the estimates of the relative treatment e
 ffects.\n\nA "have-your-cake-and-eat-it-too" solution is tentatively propo
 sed\, in which the WinBUGS "cut" function is used to make a duplicate copy
  of treatment effect parameters which have been estimated in the standard 
 way. Then\, using the same data a second time\, a model is put onto the tr
 ial baselines\, while using the duplicate treatment effects as "priors".\n
 \nExamples involving mixed treatment comparisons will be presented. We com
 pare the results obtained with different modelling assumptions\, and consi
 der alternative ways of developing predictions for a CEA from the posterio
 rs. We also explore whether this approach might be used to "link" disconne
 cted networks of randomised evidence.
LOCATION:Large Seminar Room\, 1st Floor\, Institute of Public Health\, Uni
 versity Forvie Site\, Robinson Way\, Cambridge
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