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Archive of posts filed under the Zombies category.

logit and normal are special functions, too!

I find that when people write instead of writing or when they write instead of , I wind up just having to parse the formulas back to common forms I can understand as units. So my question is the following. What’s the process for making a function an “official” special function? Is there a committee […]

When does a misunderstanding reach the point where it is recognized to be flat-out ridiculous?

James Lasdun reviews a book by Ariel Sabar telling the story of a conman who sold a fake Bible-related document to a Harvard professor, leading to academic publications and media publicity before the whole thing fell apart. The most amusing of many amusing bits: An Egyptologist at Brown University, Leo Depuydt, found a ‘colossal double […]

“Why I blog about apparent problems in science”

Nick Brown writes: In this post I want to discuss why I blog directly about what I see as errors or other problems in scientific articles. . . . I have seen criticism of the “blog first” approach because it “drops stuff on the authors out of the blue” or “doesn’t give them a right […]

More institutional failure by universities that refuse to grapple with potential research misconduct by their faculty

Last year we discussed Why We Sleep, a book that contained misrepresented data. Why We Sleep was written by a professor at the University of California. Alexey Guzey discovered many many problems with the book, including a smoking-gun graph, and Yngve Hoiseth contacted the contacted the University of California to report Walker’s violation of their […]

Your tax dollars at work (junk social science edition)

A couple people pointed me to this article: With this sort of work, I always wonder whether people who do this sort of thing really believe what they’re doing, or if they’re purposely complexifying things, the way that in chess you might try to make the board position more complex if you’re down a couple […]

We should all routinely criticize our own work.

Kerim Kavakli points me to this blog by psychology researcher Todd Kashdan who goes over his recent career and points to concerns he has with his own published work. I agree with Kavakli that this is a great thing that all of us should be doing. I did not read Kashdan’s examples in detail so […]

Headline permutations

“Trump’s Base Nurses Anger Over Election” was the headline of a story in today’s newspaper. There was something “colorless green ideas” about this headline, which made me think, Lucky Jim-style, of some permutations: Nurses Anger Trump’s Base Over Election Election Base Angers Trump Over Nurses Election Over, Trump’s Base Nurses Anger Election Over, Nurses Trump […]

“Causal Inference: The Mixtape”

A few years ago we reviewed “Mostly Harmless Econometrics,” by Josh Angrist and Jörn-Steffen Pischke. And now we have another friendly introduction to causal inference by an economist, presented as a readable paperback book with a fun title. I’m speaking of “Causal Inference: The Mixtape,” by Scott Cunningham. I like the book—all the blurbs on […]

Thinking fast, slow, and not at all: System 3 jumps the shark

By now, we’re all familiar with the three modes of thought. From wikipedia: System 1 is fast, instinctive and emotional. System 2 is slower, more deliberative, and more logical. System 3 is when you say things that sound good but make no sense. System 3 can get activated when you trust what someone tells you […]

New book coming out by Fischer Black!

Gur Huberman has the scoop. At first I was surprised to hear about this, but then I looked up Black on Wikipedia and, hey, he’s only 83, so why not write a book. He also got some prominent academics to promote it, so that’s cool.

When are Bayesian model probabilities overconfident?

Oscar Oelrich, Shutong Ding, Måns Magnusson, Aki Vehtari, and Mattias Villani write: Bayesian model comparison is often based on the posterior distribution over the set of compared models. This distribution is often observed to concentrate on a single model even when other measures of model fit or forecasting ability indicate no strong preference. Furthermore, a […]

2 reasons why the CDC and WHO were getting things wrong: (1) It takes so much more evidence to correct a mistaken claim than to establish it in the first place; (2) The implicit goal of much of the public health apparatus is to serve the health care delivery system.

Peter Dorman points to an op-ed by Zeynep Tufekci and writes: This is a high profile piece in the NY Times on why the CDC and WHO have been so resistant to the evidence for aerosol transmission. What makes it relevant is the discussion of two interacting methodological tics, the minimization of Type I error […]

The Javert paradox rears its ugly head

The Javert paradox is, you will recall, the following: Suppose you find a problem with published work. If you just point it out once or twice, the authors of the work are likely to do nothing. But if you really pursue the problem, then you look like a Javert. I labeled the paradox a few […]

Doubting the IHME claims about excess deaths by country

The Institute for Health Metrics and Evaluation at the University of Washington (IHME) was recently claiming 900,000 excess deaths, but that doesn’t appear to be consistent with the above data. These graphs are from Ariel Karlinsky, who writes: The main point of the IHME report, that total COVID deaths, estimated by excess deaths, are much […]

Blast from the past

Paul Alper points us to this news article, The Secret Tricks Hidden Inside Restaurant Menus, which is full of fun bits: There is now an entire industry known as “menu engineering”, dedicated to designing menus that convey certain messages to customers, encouraging them to spend more and make them want to come back for a […]

Indeed, the standard way that statistical hypothesis testing is taught is a 2-way binary grid. Both these dichotomies are inappropriate.

I originally gave this post the title, “New England Journal of Medicine makes the classic error of labeling a non-significant difference as zero,” but was I was writing it I thought of a more general point. First I’ll give the story, then the general point. 1. Story Dale Lehman writes: Here are an article and […]

Responding to Richard Morey on p-values and inference

Jonathan Falk points to this post by Richard Morey, who writes: I [Morey] am convinced that most experienced scientists and statisticians have internalized statistical insights that frequentist statistics attempts to formalize: how you can be fooled by randomness; how what we see can be the result of biasing mechanisms; the importance of understanding sampling distributions. […]

Thoughts inspired by “the Gospel of Jesus’s Wife”

1. Harvard’s current position on the matter This is at Harvard University’s website: But, no, it’s not a “Coptic Papyrus Fragment.” That’s a lie. Or, I guess, several years ago we could call that statement a mistake, but given that it’s been known to be false for several years, I think it’s fair to call […]

“The Multiverse of Methods: Extending the Multiverse Analysis to Address Data-Collection Decisions”

Jenna Harder writes: When analyzing data, researchers may have multiple reasonable options for the many decisions they must make about the data—for example, how to code a variable or which participants to exclude. Therefore, there exists a multiverse of possible data sets. A classic multiverse analysis involves performing a given analysis on every potential data […]

Is it really true that “the U.S. death rate in 2020 was the highest above normal since the early 1900s—even surpassing the calamity of the 1918 flu pandemic”?

tl;dr. No, it’s not true. The death rate increased by 15% from 2019 to 2020, but it jumped by 40% from 1917 to 1918. But, if so, why would anyone claim differently? Therein lies a tale. A commenter pointed to a news article with the above graphs and the following claim: The U.S. death rate […]

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