The rise of the imputers (maybe)

I thought this article in BMC Med Res Meth sounded interesting: “The rise of multiple imputation: a review of the reporting and implementation of the method in medical research“. I feel that we should know more about the adoption of analytical techniques, how they spread and are facilitated or blocked, but such reviews are almost unheard of. Unfortunately this one doesn’t answer a whole bunch of questions I have, largely because it just looks at two big-name medical journals in the years after software became widely available. I want to know what happens to get people using a new method (earlier in the history) and what gets printed all the way from top predators to bottom feeders.

rise-of-mi

Sadly, the crucial table 4, which lists the technical specifications of the methods used, is totally confusing. The half-page of miniscule footnotes (tl;dr) don’t help. All I can say is that not many of the papers used 100+ imputations, which is an interesting point because it seems recently (see a paper by Ian White which I can’t remember right now) that Don Rubin’s original experiments with a handful of imputed datasets might not be enough in some circumstances, and also with computer power on every desk (it’s not 1977 any more), there’s no reason not pump it up. Yet the original advice lives on.

It would be interesting to look at tutorial papers and reports and websites for various professions, as these are often badly written by someone who has A Little Knowledge, and see how these are referenced. I suspect a lot of people are going around referencing the original paper or the Rubin & Little book having never read either of them. Then someone should do some interviews of applied researchers who have published papers including MI. There you go, I’ve just given you a PhD topic. Off and do the thing.

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Filed under Bayesian, computing, healthcare

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