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Upholding the patriarchy, one blog post at a time

A white male writes: Your recent post reminded me: partly because of your previous posts, I spent a fair amount of the last two years reading Updike, whom I’d never read before. It was time well spent. Thank you for mentioning him in your blog from time to time. I find early Updike to be […]

Big trouble coming with the 2020 Census

OK, first things first. For readers of this blog who live in the United States: Don’t forget to fill out your census. They’re doing in online, and you should’ve received a letter in the mail last month telling you how to do it. And now the news. Dr. Z points us to this post by […]

Webinar on approximate Bayesian computation

X points us to this online seminar series which is starting this Thursday! Some speakers and titles of talks are listed. I just wish I could click on the titles and see the abstracts and papers! The seminar is at the University of Warwick in England, which is not so convenient—I seem to recall that […]

“The Generalizability Crisis” in the human sciences

In an article called The Generalizability Crisis, Tal Yarkoni writes: Most theories and hypotheses in psychology are verbal in nature, yet their evaluation overwhelmingly relies on inferential statistical procedures. The validity of the move from qualitative to quantitative analysis depends on the verbal and statistical expressions of a hypothesis being closely aligned—that is, that the […]

BDA FREE (Bayesian Data Analysis now available online as pdf)

Our book, Bayesian Data Analysis, is now available for download for non-commercial purposes! You can find the link here, along with lots more stuff, including: • Aki Vehtari’s course material, including video lectures, slides, and his notes for most of the chapters • 77 best lines from my course • Data and code • Solutions […]

Pandemic cats following social distancing

Who ever said that every post had to do with statistical modeling, causal inference or social science? (Above photo sent in by Zad.)

Career advice for a future statistician

Gary Ruiz writes: I am a first-year math major at the Los Angeles City College in California, and my long-term educational plans involve acquiring at least one graduate degree in applied math or statistics. I’m writing to ask whether you would offer any career advice to someone interested in future professional work in statistics. I […]

Interesting y-axis

Merlin sent along this one: P.S. To be fair, when it comes to innumeracy, whoever designed the above graph has nothing on these people. As Clarissa Jan-Lim put it: Math is hard and everyone needs to relax! (Also, Mr. Bloomberg, sir, I think we will all still take $1.53 if you’re offering).

Model building is Lego, not Playmobil. (toward understanding statistical workflow)

John Seabrook writes: Socrates . . . called writing “visible speech” . . . A more contemporary definition, developed by the linguist Linda Flower and the psychologist John Hayes, is “cognitive rhetoric”—thinking in words. In 1981, Flower and Hayes devised a theoretical model for the brain as it is engaged in writing, which they called […]

Noise-mining as standard practice in social science

The following example is interesting, not because it is particularly noteworthy but rather because it represents business as usual in much of social science: researchers trying their best, but hopelessly foiled by their use of crude psychological theories and cruder statistics, along with patterns of publication and publicity that motivate the selection and interpretation of […]

Conference on Mister P online tomorrow and Saturday, 3-4 Apr 2020

We have a conference on multilevel regression and poststratification (MRP) this Friday and Saturday, organized by Lauren Kennedy, Yajuan Si, and me. The conference was originally scheduled to be at Columbia but now it is online. Here is the information. If you want to join the conference, you must register for it ahead of time; […]

More coronavirus research: Using Stan to fit differential equation models in epidemiology

Seth Flaxman and others at Imperial College London are using Stan to model coronavirus progression; see here (and I’ve heard they plan to fix the horrible graphs!) and this Github page. They also pointed us to this article from December 2019, Contemporary statistical inference for infectious disease models using Stan, by Anastasia Chatzilena et al. […]

What can we learn from super-wide uncertainty intervals?

This question comes up a lot, in one form or another. Here’s a topical version, from Luigi Leone: I am writing after three weeks of lockdown. I would like to put to your attention this Imperial College report (issued on monday, I believe). The report estimates 9.8% of the Italian population (thus, 6 mil) and […]

“Partially Identified Stan Model of COVID-19 Spread”

Robert Kubinec writes: I am working with a team collecting government responses to the coronavirus epidemic. As part of that, I’ve designed a Stan time-varying latent variable model of COVID-19 spread that only uses observed tests and cases. I show while it is impossible to know the true number of infected cases, we can rank/sign […]

Moving blog to twitter

My co-bloggers and I have decided that the best discussions are on twitter so we’re shutting down this blog, as of today. Old posts will remain, and you can continue to comment, but we won’t be adding any new material. We’re doing this for two reasons: 1. Our various attempts to raise funds by advertising […]

Stasi’s back in town. (My last post on Cass Sunstein and Richard Epstein.)

OK, I promise, this will be the last Stasi post ever. tl;dr: This post is too long. Don’t read it.

“How to be Curious Instead of Contrarian About COVID-19: Eight Data Science Lessons From Coronavirus Perspective”

Rex Douglass writes: I direct the Machine Learning for Social Science Lab at the Center for Peace and Security Studies, UCSD. I’ve been struggling with how non-epidemiologists should contribute to COVID-19 questions right now, and I wrote a short piece that summarizes my thoughts. 8 data science suggestions For people who want to use theories […]

Fit nonlinear regressions in R using stan_nlmer

This comment from Ben reminded me that lots of people are running nonlinear regressions using least squares and other unstable methods of point estimation. You can do better, people! Try stan_nlmer, which fits nonlinear models and also allows parameters to vary by groups. I think people have the sense that maximum likelihood or least squares […]

Structural equation modeling and Stan

Eric Brown asks: How does Stan and its Bayesian modeling relate to structural equation modeling? Do you know of a resource that attempts to explain the concepts behind SEM in terms of Stan nomenclature and concepts? Some research that I’ve looked into uses SEM to evaluate latent factors underlying multiple measurements with associated errors; or […]

The second derivative of the time trend on the log scale (also see P.S.)

Peter Dorman writes: Have you seen this set of projections? It appears to have gotten around a bit, with citations to match, and IHME Director Christopher Murray is a superstar. (WHO Global Burden of Disease) Anyway, I live in Oregon, and when you compare our forecast to New York State it gets weird: a resource […]