Bert Gunter writes:
You may already have seen this [“Harking, Sharking, and Tharking: Making the Case for Post Hoc Analysis of Scientific Data,” John Hollenbeck, Patrick Wright]. It discusses many of the same themes that you and others have highlighted in the special American Statistician issue and elsewhere, but does so from a slightly different perspective, which I thought you might find interesting. I believe it provides some nice examples of what Chris Tong called “enlightened description” in his American Statistician piece.
I replied that Hollenbeck and Wright’s claims seem noncontroversial. I’ve tharked in every research project I’ve ever done.
I also clicked through and read the Tong paper, “Statistical Inference Enables Bad Science; Statistical Thinking Enables Good Science.” The article is excellent—starting with its title—and it brings up many thoughts. I’ll devote an entire post to it.
Also I was amused by this, the final sentence of Tong’s article:
More generally, if we had to recommend just three articles that capture the spirit of the overall approach outlined here, they would be (in chronological order) Freedman (1991), Gelman and Loken (2014), and Mogil and Macleod (2017).
If Freedman were to see this sentence, he’d spin in his grave. He absolutely despised me, and he put in quite a bit of effort to convince himself and others that my work had no value.
Tomorrow’s post: “Statistical Inference Enables Bad Science; Statistical Thinking Enables Good Science”