We always talk about how hard it is to actually try and verify the assumptions required for missing data techniques to yield unbiased answers. Still, it really is a breath of fresh air when somebody tries to give some (data driven) guidance on whether or not an assumption really is reasonable. That was the case with a recent PDS article:
Marston L, Carpenter JR, Walters KR, Morris RW, Nazareth I, Petersen I. Issues in multiple imputation of missing data for large general practice clinical databases. Pharmacoepidemiol Drug Saf 2010 (currently an epub)
They nicely make the case that blood pressure data is likely to be missing at random in these databases. Given my thoughts that BP data is underused, this is actually a pretty major advance as it allows more confidence in inferences from these large clinical databases.
Good show, folks!
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