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“Priming Effects Replicate Just Fine, Thanks”

I came across this 2012 post by John Bargh who does not seem to be happy about the failures of direct replications of his much-cited elderly-words-and-slow-walking study. What strikes me about Bargh’s comments is how they illustrate the moving-target approach to much of science. Here’s the quick story. In 1996, Bargh, Chen, and Burrows published […]

Arrow’s Theorem in the news: Sleazy-ass political scientists cut-and-paste their way to 3 publications from the same material

I’m posting this one in the evening because I know some people just hate when I write about plagiarism. But this one is so ridiculous I had to share it with you. John Smith (or maybe I should say “John Smith”?) writes: Today on a political science forum I saw this information about plagiarism by […]

In general, hypothesis testing is overrated and hypothesis generation is underrated, so it’s fine for these data to be collected with exploration in mind.

In preparation for writing this news article, Kelly Servick asked me what I thought about the Kavli HUMAN Project (see here and here). Here’s what I wrote: The general idea of gathering comprehensive data seems reasonable to me. I’ve often made the point that careful data collection and measurement are important. Data analysis is the […]

Scientific explanation of Panther defeat!

Roy’s comment on our recent post inspires me to reveal the true explanation underlying the Carolina team’s shocking Super Bowl loss. The Panthers were primed during the previous week with elderly-themed words such as “bingo” and “Manning.” As well-established research has demonstrated, this caused Cam and the gang to move more slowly, hence all the […]

Stan’s Super Bowl prediction: Broncos 24, Panthers 13

We ran the data through our model, not just the data from the past season but from the past 17 seasons (that’s what we could easily access) with a Gaussian process model to allow team abilities to vary over time. Because we’re modeling individual game outcomes, our model automatically controls for imbalances such as Carolina’s […]

Primed to lose

David Hogg points me to a recent paper, “A Social Priming Data Set With Troubling Oddities” by Hal Pashler, Doug Rohrer, Ian Abramson, Tanya Wolfson, and Christine Harris, which begins: Chatterjee, Rose, and Sinha (2013) presented results from three experiments investigating social priming—specifically, priming effects induced by incidental exposure to concepts relating to cash or […]

Forking paths vs. six quick regression tips

Bill Harris writes: I know you’re on a blog delay, but I’d like to vote to raise the odds that my question in a comment to http://andrewgelman.com/2015/09/15/even-though-its-published-in-a-top-psychology-journal-she-still-doesnt-believe-it/gets discussed, in case it’s not in your queue. It’s likely just my simple misunderstanding, but I’ve sensed two bits of contradictory advice in your writing: fit one complete model all at […]

On deck this week

Mon: Forking paths vs. six quick regression tips Tues: Primed to lose Wed: Point summary of posterior simulations? Thurs: In general, hypothesis testing is overrated and hypothesis generation is underrated, so it’s fine for these data to be collected with exploration in mind. Fri: “Priming Effects Replicate Just Fine, Thanks” Sat: Pooling is relative to […]

You’ll never guess what I say when I have nothing to say

A reporter writes: I’m a reporter working on a story . . . and I was wondering if you could help me out by taking a quick look at the stats in the paper it’s based on. The paper is about paedophiles being more likely to have minor facial abnormalities, suggesting that paedophilia is a […]

What’s the difference between randomness and uncertainty?

Julia Galef mentioned “meta-uncertainty,” and how to characterize the difference between a 50% credence about a coin flip coming up heads, vs. a 50% credence about something like advanced AI being invented this century. I wrote: Yes, I’ve written about this probability thing. The way to distinguish these two scenarios is to embed each of […]

The bejeezus

Tova Perlmutter writes of a recent online exchange:

Stat Podcast Plan

In my course on Statistical Communication and Graphics, each class had a special guest star who would answer questions on his or her area of expertise. These were not “guest lectures”—there were specific things I wanted the students to learn in this course, it wasn’t the kind of seminar where they just kick back each […]

The Notorious N.H.S.T. presents: Mo P-values Mo Problems

Alain Content writes: I am a psycholinguist who teaches statistics (and also sometimes publishes in Psych Sci). I am writing because as I am preparing for some future lessons, I fall back on a very basic question which has been worrying me for some time, related to the reasoning underlying NHST [null hypothesis significance testing]. […]

“Chatting with the Tea Party”

I got an email last month offering two free tickets to the preview of a new play, Chatting with the Tea Party, described as “a documentary-style play about a New York playwright’s year attending Tea Party meetings around the country and interviewing local leaders. Nothing the Tea Party people in the play say has been […]

Where the fat people at?

Pearly Dhingra points me to this article, “The Geographic Distribution of Obesity in the US and the Potential Regional Differences in Misreporting of Obesity,” by Anh Le, Suzanne Judd, David Allison, Reena Oza-Frank, Olivia Affuso, Monika Safford, Virginia Howard, and George Howard, who write: Data from BRFSS [the behavioral risk factor surveillance system] suggest that […]

Hey—go to Iceland and work on glaciers!

Egil Ferkingstad and Birgir Hrafnkelsson write: We have an exciting PhD position here at the University of Iceland on developing Bayesian hierarchical spatio-temporal models to the field of glaciology. Havard Rue at NTNU, Trondheim and Chris Wikle at the University of Missouri will also be part of the project. The Department of Mathematics at the […]

Stunning breakthrough: Using Stan to map cancer screening!

Paul Alper points me to this article, Breast Cancer Screening, Incidence, and Mortality Across US Counties, by Charles Harding, Francesco Pompei, Dmitriy Burmistrov, Gilbert Welch, Rediet Abebe, and Richard Wilson. Their substantive conclusion is there’s too much screening going on, but here I want to focus on their statistical methods: Spline methods were used to […]

When does peer review make no damn sense?

Disclaimer: This post is not peer reviewed in the traditional sense of being vetted for publication by three people with backgrounds similar to mine. Instead, thousands of commenters, many of whom are not my peers—in the useful sense that, not being my peers, your perspectives are different from mine, and you might catch big conceptual […]

On deck this week

Mon: When does peer review make no damn sense? Tues: Stunning breakthrough: Using Stan to map cancer screening! Wed: Where the fat people at? Thurs: The Notorious N.H.S.T. presents: Mo P-values Mo Problems Fri: What’s the difference between randomness and uncertainty? Sat: You’ll never guess what I say when I have nothing to say Sun: […]

Ted Cruz angling for a position in the Stanford poli sci department

In an amusing alignment of political and academic scandals, presidential candidate Ted Cruz was blasted for sending prospective voters in the Iowa Caucus this misleading mailer: Which reminds me of the uproar two years ago when a couple of Stanford political science professors sent prospective Montana voters this misleading mailer: I don’t know which is […]