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As mentioned in response to original tweet, if you stratify (e.g. by centre) then you must adjust. https://t.co/c58vN1Yk6l and https://t.co/xrxVan08nf
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@ADAlthousePhD @tmorris_mrc @JasonConnorPhD @KertViele Here's the simulation study i did on it. My view: if you expect centre to have a strong prognostic effect, then adjust using random intercept models/GEEs https://t.co/3S0zU7Oa4N
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@DavidAttwood12 @adamgordon1978 @VickiG_physio @SVH00 Would want to consider if it would be cluster or individually randomised? S.Eldridge has published widely on CRTs design (https://t.co/0ysTk3yyOF). Some other potentially interesting reads: https://t.co
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@beagoulao @tmorris_mrc Sorry, not aware of one; our paper on multicentre trials with binary outcomes may deal with some similar issues (e.g. the problems associated with adjustment for centre with a GLM), though I'm sure there are other issues specific to
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Do random-effects models make a difference in multicentre trials? http://t.co/SxodfKxlU7 http://t.co/ezy5dPoM0D http://t.co/nj2SwO2DUq
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@stephensenn @ChristosArgyrop Surely this depends on the number of patients? W/ binary outcome, could lead to bias. http://t.co/ezy5dPoM0D
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Do random-effects models make a difference in multicentre trials? http://t.co/SxodfKxlU7 http://t.co/ezy5dPoM0D http://t.co/nj2SwO2DUq
1,185 followers
Do random-effects models make a difference in multicentre trials? http://t.co/SxodfKxlU7 http://t.co/ezy5dPoM0D http://t.co/nj2SwO2DUq