2) Krauss spends much time discussing the issue of “achieving good balance” in RCTs
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2a) this has been discussed at great length previously by Altman, Senn, and others over the years
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2b) For example, here:https://onlinelibrary.wiley.com/doi/abs/10.1002/sim.5713 …
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2c) I also like this quote from a more recent piece:https://www.ncbi.nlm.nih.gov/pubmed/29518478
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2d) “Under proper random treatment assignment, distributions and imbalances of all baseline covariates among treatment groups are random. Therefore, random baseline covariate imbalances and random treatment assignments must be accepted or rejected, together.”
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2e) “Pursuing perfect baseline covariate balancing under the name of randomized controlled trial is self-deception. Random baseline covariate imbalances can and should be taken care of by statistical approaches. Perfect baseline covariate balance is not necessary.”
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3) Continuing with the balance issue: even after the corrigendum, the piece still contains this troubled statement in the conclusion
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3a) “No researcher should thus just generate a single randomisation schedule and then use it to run an experiment.”
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3b) “Instead researchers need to run a set of randomisation iterations before conducting a trial and select the one with the most balanced distribution of background influencers between trial groups”
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3c) Putting aside whether balance is necessary, this is not remotely feasible in the majority of RCTs in medicine. It is maddening that this statement went past peer review unchallenged.
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Yes I'm very confused here. That obviously introduces an enormous potential for bias where researchers choose their favorite set of randomization results
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Replying to @ADAlthousePhD
I mean, half of the point of randomization is removing researcher selection bias and they want to reintroduce it?
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