James Heathers reports on the article, “Contagion or restitution? When bad apples can motivate ethical behavior,” by Gino, Gu, and Zhong (2009): There is some sentiment data reported in Experiment 3, which seems to be reported in whole units. They also indicated how guilty they would feel about the behavior of the person who took all the money along with some unrelated emotional measures (1 = not at all, 5 = very much)… participants in the in-group selfish condition felt more guilty (M = 4.61, SD = 1.64) about the person’s selfish behavior than the participants in the out-group selfish condi ..read more

I came across this post from 2011, “Infovis, infographics, and data visualization: Where I’m coming from, and where I’d like to go,” and it seemed to make sense to reassess where we are now, 12 years later. From 2011: I majored in physics in college and I worked in a couple of research labs during the summer. Physicists graph everything. I did most of my plotting on graph paper–this continued through my second year of grad school–and became expert at putting points at 1/5, 2/5, 3/5, and 4/5 between the x and y grid lines. In grad school in statistics, I continued my physics habits and graphed ..read more

I’m coding up a new adaptive sampler in Python, which is super exciting (the basic methodology is due to Nawaf Bou-Rabee and Tore Kleppe). Luckily for me, another great colleague, Edward Roualdes, has been keeping me on the straight and narrow by suggesting stronger tests and pointing out actual bugs in the repository (we’ll open access it when we put the arXiv paper up—hopefully by the end of the month). There are a huge number of potential fencepost (off by one), log-vs-exponential, positive-vs-negative, numerator-vs-denominator, and related errors to make in this kind of thing. For example ..read more

It’s standard practice in research articles as well as editorials in scholarly journals to present just one side of an issue. That’s how it’s done! A typical research article looks like this: “We found X. Yes, we really found X. Here are some alternative explanations for our findings that don’t work. So, yeah, it’s really X, it can’t reasonably be anything else. Also, here’s why all the thickheaded previous researchers didn’t already find X. They were wrong, though, we’re right. It’s X. Indeed, it had to be X all along. X is the only possibility that makes sense. But it’s a discovery, it’s ab ..read more

Enjoy. They looked at least 12 cognitive outcomes, one of which had p = 0.02, but other differences “were just shy of statistical significance.” Also: The degree of change in the brain measure was not significantly correlated with the degree of change in the behavioral measure (p > 0.05) but this may be due to the reduced power in this analysis which necessarily only included the smaller subset of individuals who completed neuropsychological assessments during in-person visits. This is one of the researcher degrees of freedom we see all the time: an analysis with p > 0.05 can be labele ..read more

This is all super-simple; still, it might be useful. In class today a student asked for some intuition as to why, when you’re regressing y on x, measurement error on x biases the coefficient estimate by measurement error on y does not. I gave the following quick explanation: – You’re already starting with the model, y_i = a + bx_i + e_i. If you add measurement error to y, call it y*_i = y_i + eta_i, and then you regress y* on x, you can write y* = a + bx_i + e_i + eta_i, and as long as eta is independent of e, you can just combine them into a single error term. – When you have measurement err ..read more

I had dinner a few nights ago with Andrew’s former postdoc Aleks Jakulin, who left the green fields of academia for entrepreneurship ages ago. Aleks was telling me he was impressed by the new LLMs, but then asserted that they’re clearly not intelligent. This reminded me of the old saw in AI that “AI is whatever a machine can’t do.” In the end, the definition of “intelligent” is a matter of semantics. Semantics is defined by conventional usage, not by fiat (the exception seems to be an astronomical organization trying to change the definition of “planet” to make it more astronomically precise ..read more

I keep worrying, as with a loose tooth, about news media elites who are going for the UFOs-as-space-aliens theory. This one falls halfway between election denial (too upsetting for me to want to think about too often) and belief in ghosts (too weird to take seriously). I was also thinking about the movie JFK, which I saw when it came out in 1991. As a reader of the newspapers, I knew that the narrative pushed in the movie was iffy, to say the least; still, I watched the movie intently—I wanted to believe. In the same way that in the 1970s I wanted to believe those claims that dolphins are smar ..read more

Colby Vorland writes: In case it is of interest, a paper we reported 3 years, 4 months ago was just retracted: Retracted: Effect of Moderate-Intensity Aerobic Exercise on Hepatic Fat Content and Visceral Lipids in Hepatic Patients with Diabesity: A Single-Blinded Randomised Controlled Trial https://www.hindawi.com/journals/ecam/2023/9829387/ Over this time, I was sent draft retraction notices on two occasions by Hindawi’s research integrity team that were then reneged for reasons that were not clear. The research integrity team stopped responding to me, but after I involved COPE, they eventua ..read more

19 W 4th Street, Room 517: How large is that treatment effect, really? Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University “Unbiased estimates” aren’t really unbiased, for a bunch of reasons, including aggregation, selection, extrapolation, and variation over time. Econometrics typically focus on causal identification, with this goal of estimating “the” effect. But we typically care about individual effects (not “Does the treatment work?” but “Where and when does it work?” and “Where and when does it hurt?”). Estimating individual effects is releva ..read more