Victory!

We submitted a paper to a leading statistics journal, and one of the review reports included the following sentence:

Although the statistical methodology used is not particularly complex, sometimes a straightforward solution to a problem can be even more elegant than something that is technically more impressive.

At first I was a little miffed that they referred to our methods as “not particularly complex” but then I realized that this is really a victorious moment for applied Bayesian data analysis. Our paper used multilevel modeling, an adaptive Gibbs/Metropolis algorithm, posterior predictive checking, as well as tons of graphs and postprocessing of inferences.

Not too many years ago, we would have had to deal with generalized skepticism about Bayes, prior distributions, exchangeability, blah blah blah. Maybe even some objection to using a probability model at all. (One of my colleagues where I used to work once told me, “We don’t believe in models.”) And the reviewers who liked the paper would have gone on about how innovative it was. It’s good to be able to skip over all that and go straight to the modeling (the “science,” as Rubin would put it).

2 thoughts on “Victory!

  1. Congratulations! I don't suppose that when it's published, they'll let you post a copy here, eh? I'd like to do this with my own papers, (once I write them — details…) but I suspect that the publishers wouldn't be too keen on it.

  2. The crossover point came IMO when they produced an Excel add-in for BUGS. It can't be difficult statistics if you can do it in Excel!

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