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Prior choice recommendations wiki !

Here’s the wiki, and here’s the background: Our statistical models are imperfect compared to the true data generating process and our complete state of knowledge (from an informational-Bayesian perspective) or the set of problems over which we wish to average our inferences (from a population-Bayesian or frequentist perspective). The practical question here is what model […]

A whole fleet of Wansinks: is “evidence-based design” a pseudoscience that’s supporting a trillion-dollar industry?

Following a recent post that mentioned

“Data sleaze: Uber and beyond”

Interesting discussion from Kaiser Fung. I don’t have anything to add here; it’s just a good statistics topic. Scroll through Kaiser’s blog for more: Dispute over analysis of school quality and home prices shows social science is hard My pre-existing United boycott, and some musing on randomness and fairness etc.

Using prior knowledge in frequentist tests

Christian Bartels send along this paper, which he described as an attempt to use informative priors for frequentist test statistics. I replied: I’ve not tried to follow the details but this reminds me of our paper on posterior predictive checks. People think of this as very Bayesian but my original idea when doing this research […]

I hate R, volume 38942

R doesn’t allow block comments. You have to comment out each line, or you can encapsulate the block in if(0){} which is the world’s biggest hack. Grrrrr. P.S. Just to clarify: I want block commenting not because I want to add long explanatory blocks of text to annotate my scripts. I want block commenting because […]

The next Lancet retraction? [“Subcortical brain volume differences in participants with attention deficit hyperactivity disorder in children and adults”]

Someone who prefers to remain anonymous asks for my thoughts on this post by Michael Corrigan and Robert Whitaker, “Lancet Psychiatry Needs to Retract the ADHD-Enigma Study: Authors’ conclusion that individuals with ADHD have smaller brains is belied by their own data,” which begins: Lancet Psychiatry, a UK-based medical journal, recently published a study titled […]

Stan without frontiers, Bayes without tears

This recent comment thread reminds me of a question that comes up from time to time, which is how to teach Bayesian statistics to students who aren’t comfortable with calculus. For continuous models, probabilities are integrals. And in just about every example except the one at 47:16 of this video, there are multiple parameters, so […]

The meta-hype algorithm

Kevin Lewis pointed me to this article: There are several methods for building hype. The wealth of currently available public relations techniques usually forces the promoter to judge, a priori, what will likely be the best method. Meta-hype is a methodology that facilitates this decision by combining all identified hype algorithms pertinent for a particular […]

Would you prefer three N=300 studies or one N=900 study?

Stephen Martin started off with a question: I’ve been thinking about this thought experiment: — Imagine you’re given two papers. Both papers explore the same topic and use the same methodology. Both were preregistered. Paper A has a novel study (n1=300) with confirmed hypotheses, followed by two successful direct replications (n2=300, n3=300). Paper B has […]

Drug-funded profs push drugs

Someone who wishes to remain anonymous writes: I just read a long ProPublica article that I think your blog commenters might be interested in. It’s from February, but was linked to by the Mad Biologist today (https://mikethemadbiologist.com/). Here is a link to the article: https://www.propublica.org/article/big-pharma-quietly-enlists-leading-professors-to-justify-1000-per-day-drugs In short, it’s about a group of professors (mainly economists) […]

Journals for insignificant results

Tom Daula writes: I know you’re not a fan of hypothesis testing, but the journals in this blog post are an interesting approach to the file drawer problem. I’ve never heard of them or their like. An alternative take (given academia standard practice) is “Journal for XYZ Discipline papers that p-hacking and forking paths could […]

Teaching Statistics: A Bag of Tricks (second edition)

Hey! Deb Nolan and I finished the second edition of our book, Teaching Statistics: A Bag of Tricks. You can pre-order it here. I love love love this book. As William Goldman would say, it’s the “good parts version”: all the fun stuff without the standard boring examples (counting colors of M&M’s, etc.). Great stuff […]

My proposal for JASA: “Journal” = review reports + editors’ recommendations + links to the original paper and updates + post-publication comments

Whenever they’ve asked me to edit a statistics journal, I say no thank you because I think I can make more of a contribution through this blog. I’ve said no enough times that they’ve stopped asking me. But I’ve had an idea for awhile and now I want to do it. I think that journals […]

My talk this Friday in the Machine Learning in Finance workshop

This is kinda weird because I don’t know anything about machine learning in finance. I guess the assumption is that statistical ideas are not domain specific. Anyway, here it is: What can we learn from data? Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University The standard framework for statistical inference leads […]

Reputational incentives and post-publication review: two (partial) solutions to the misinformation problem

So. There are erroneous analyses published in scientific journals and in the news. Here I’m not talking not about outright propaganda, but about mistakes that happen to coincide with the preconceptions of their authors. We’ve seen lots of examples. Here are just a few: – Political scientist Larry Bartels is committed to a model of […]

Donald Trump’s nomination as an unintended consequence of Citizens United

The biggest surprise of the 2016 election campaign was Donald Trump winning the Republican nomination for president. A key part of the story is that so many of the non-Trump candidates stayed in the race so long because everyone thought Trump was doomed, so they were all trying to grab Trump’s support when he crashed. […]

“Do you think the research is sound or is it gimmicky pop science?”

David Nguyen writes: I wanted to get your opinion on http://www.scienceofpeople.com/. Do you think the research is sound or is it gimmicky pop science? My reply: I have no idea. But since I see no evidence on the website, I’ll assume it’s pseudoscience until I hear otherwise. I won’t believe it until it has the […]

Organizations that defend junk science are pitiful suckers get conned and conned again

So. Cornell stands behind Wansink, and Ohio State stands behind Croce. George Mason University bestows honors on Weggy. Penn State trustee disses “so-called victims.” Local religious leaders aggressively defend child abusers in their communities. And we all remember how long it took for Duke University to close the door on Dr. Anil Potti. OK, I […]

Causal inference conference in North Carolina

Michael Hudgens announces: Registration for the 2017 Atlantic Causal Inference Conference is now open. The registration site is here. More information about the conference, including the poster session and the Second Annual Causal Inference Data Analysis Challenge can be found on the conference website here. We held the very first Atlantic Causal Inference Conference here at Columbia […]

The Efron transition? And the wit and wisdom of our statistical elders

Stephen Martin writes: Brad Efron seems to have transitioned from “Bayes just isn’t as practical” to “Bayes can be useful, but EB is easier” to “Yes, Bayes should be used in the modern day” pretty continuously across three decades. http://www2.stat.duke.edu/courses/Spring10/sta122/Handouts/EfronWhyEveryone.pdf http://projecteuclid.org/download/pdf_1/euclid.ss/1028905930 http://statweb.stanford.edu/~ckirby/brad/other/2009Future.pdf Also, Lindley’s comment in the first article is just GOLD: “The last example […]