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Archive of posts filed under the Zombies category.

Statmodeling Retro

As many of you know, this blog auto-posts on twitter. That’s cool. But we also have 15 years of old posts with lots of interesting content and discussion! So I had this idea of setting up another twitter feed, Statmodeling Retro, that would start with our very first post in 2004 and then go forward, […]

More on that horrible statistical significance grid

Regarding this horrible Table 4: Eric Loken writes: The clear point or your post was that p-values (and even worse the significance versus non-significance) are a poor summary of data. The thought I’ve had lately, working with various groups of really smart and thoughtful researchers, is that Table 4 is also a model of their […]

The bullshit asymmetry principle

Jordan Anaya writes, “We talk about this concept a lot, I didn’t realize there was a name for it.” From the wikipedia entry: Publicly formulated the first time in January 2013 by Alberto Brandolini, an Italian programmer, the bullshit asymmetry principle (also known as Brandolini’s law) states that: The amount of energy needed to refute […]

What should JPSP have done with Bem’s ESP paper, back in 2010? Click to find the surprisingly simple answer!

OK, you all remember the story, arguably the single event that sent the replication crisis into high gear: the decision of the Journal of Personality and Social Psychology to publish a paper on extra-sensory perception (ESP) by Cornell professor Daryl Bem and the subsequent discussion of this research in the New York Times and elsewhere. […]

When doing regression (or matching, or weighting, or whatever), don’t say “control for,” say “adjust for”

This comes up from time to time. We were discussing a published statistical blunder, an innumerate overconfident claim arising from blind faith that a crude regression analysis would control for various differences between groups. Martha made the following useful comment: Another factor that I [Martha] believe tends to promote the kind of thing we’re talking […]

Just when you thought it was safe to go back into the water . . . SHARK ATTACKS in the Journal of Politics

We’ve been here before. Back in 2002, political scientists Chris Achen and Larry Bartels presented a paper “Blind Retrospection – Electoral Responses to Drought, Flu and Shark Attacks.” Here’s a 2012 version in which the authors trace “the electoral impact of a clearly random event—a dramatic series of shark attacks in New Jersey in 1916” […]

The butterfly effect: It’s not what you think it is.

John Cook writes: The butterfly effect is the semi-serious claim that a butterfly flapping its wings can cause a tornado half way around the world. It’s a poetic way of saying that some systems show sensitive dependence on initial conditions, that the slightest change now can make an enormous difference later . . . Once […]

A ladder of responses to criticism, from the most responsible to the most destructive

In a recent discussion thread, I mentioned how I’m feeling charitable toward David Brooks, Michael Barone, and various others whose work I’ve criticized over the years, because their responses have been so civilized and moderate. Consider the following range of responses to an outsider pointing out an error in your published work: 1. Look into […]

How post-hoc power calculation is like a shit sandwich

Damn. This story makes me so frustrated I can’t even laugh. I can only cry. Here’s the background. A few months ago, Aleksi Reito (who sent me the adorable picture above) pointed me to a short article by Yanik Bababekov, Sahael Stapleton, Jessica Mueller, Zhi Fong, and David Chang in Annals of Surgery, “A Proposal […]

MRP (multilevel regression and poststratification; Mister P): Clearing up misunderstandings about

Someone pointed me to this thread where I noticed some issues I’d like to clear up: David Shor: “MRP itself is like, a 2009-era methodology.” Nope. The first paper on MRP was from 1997. And, even then, the component pieces were not new: we were just basically combining two existing ideas from survey sampling: regression […]

On deck for the first half of 2019

OK, this is what we’ve got for you: “The Book of Why” by Pearl and Mackenzie Reproducibility and Stan MRP (multilevel regression and poststratification; Mister P): Clearing up misunderstandings about Becker on Bohm on the important role of stories in science This is one offer I can refuse How post-hoc power calculation is like a […]

What to do when you read a paper and it’s full of errors and the author won’t share the data or be open about the analysis?

Someone writes: I would like to ask you for an advice regarding obtaining data for reanalysis purposes from an author who has multiple papers with statistical errors and doesn’t want to share the data. Recently, I reviewed a paper that included numbers that had some of the reported statistics that were mathematically impossible. As the […]

Authority figures in psychology spread more happy talk, still don’t get the point that much of the published, celebrated, and publicized work in their field is no good (Part 2)

Part 1 was here. And here’s Part 2. Jordan Anaya reports: Uli Schimmack posted this on facebook and twitter. I [Anaya] was annoyed to see that it mentions “a handful” of unreliable findings, and points the finger at fraud as the cause. But then I was shocked to see the 85% number for the Many […]

A couple of thoughts regarding the hot hand fallacy fallacy

For many years we all believed the hot hand was a fallacy. It turns out we were all wrong. Fine. Such reversals happen. Anyway, now that we know the score, we can reflect on some of the cognitive biases that led us to stick with the “hot hand fallacy” story for so long. Jason Collins […]

Latour Sokal NYT

Alan Sokal writes: I don’t know whether you saw the NYT Magazine’s fawning profile of sociologist of science Bruno Latour about a month ago. I wrote to the author, and later to the editor, to critique the gross lack of balance (and even of the most minimal fact-checking). No reply. So I posted my critique […]

Niall Ferguson and the perils of playing to your audience

History professor Niall Ferguson had another case of the sillies. Back in 2012, in response to Stephen Marche’s suggestion that Ferguson was serving up political hackery because “he has to please corporations and high-net-worth individuals, the people who can pay 50 to 75K to hear him talk,” I wrote: But I don’t think it’s just […]

These 3 problems destroy many clinical trials (in context of some papers on problems with non-inferiority trials, or problems with clinical trials in general)

Paul Alper points to this news article in Health News Review, which says: A news release or story that proclaims a new treatment is “just as effective” or “comparable to” or “as good as” an existing therapy might spring from a non-inferiority trial. Technically speaking, these studies are designed to test whether an intervention is […]

“Using numbers to replace judgment”

Julian Marewski and Lutz Bornmann write: In science and beyond, numbers are omnipresent when it comes to justifying different kinds of judgments. Which scientific author, hiring committee-member, or advisory board panelist has not been confronted with page-long “publication manuals”, “assessment reports”, “evaluation guidelines”, calling for p-values, citation rates, h-indices, or other statistics in order to […]

The State of the Art

Christie Aschwanden writes: Not sure you will remember, but last fall at our panel at the World Conference of Science Journalists I talked with you and Kristin Sainani about some unconventional statistical methods being used in sports science. I’d been collecting material for a story, and after the meeting I sent the papers to Kristin. […]

Robustness checks are a joke

Someone pointed to this post from a couple years ago by Uri Simonsohn, who correctly wrote: Robustness checks involve reporting alternative specifications that test the same hypothesis. Because the problem is with the hypothesis, the problem is not addressed with robustness checks. Simonsohn followed up with an amusing story: To demonstrate the problem I [Simonsohn] […]