Those correction notices, in full. (Yes, it’s possible to directly admit and learn from error.)

Statistical Modeling, Causal Inference, and Social Science 2024-11-24

In light of our recent discussion of the unwillingness of authors of published papers to acknowledge their mistakes, I thought I’d post the four correction notices that I’ve felt the need to issue.

From 1999, correcting a paper that appeared in 1993:

From 2013, correcting a paper that appeared in 2008:

From 2017, correcting a paper that appeared in 2006:

Finally, there was this note from 2014 correcting a paper from 1996 that had been published in a volume, not a journal. There was no way to issue a formal correction notice for an already-published book, so I posted the correction on the blog. It’s an interesting story—in short, in the paper we said we’d done something that we’d never done, and we made a false statement. In the correction notice, I confirmed with a simple simulation in R that we’d indeed made a mistake.

Discussion

I like how the correction notices are so crisp and un-hedging. We got it wrong, that’s the story!

The only thing I regret is that about these notices is that I don’t explore how the mistakes happened. If I could do it all over, I’d add a sentence to each, on what aspect of our workflow failed so as to enable the error.

Here goes, to be appended to the published correction notices above:

1999: It is not clear to us in general how to avoid this sort of false proof, the problem being that the false statement seemed so natural to us that we did not think to look at it carefully.

2013: It seems likely that we could have avoided this error with a better data-analysis workflow making graphs of the correlations between all pairs of variables, along with a computational workflow that would have made it easier to correct the problem.

2017: We might have caught this problem had the paper included a fully worked example with code.

Not perfect, but you get the idea.