Shreeharsh Kelkar writes: As a regular reader of your blog, I wanted to ask you if you had taken a look at the recent debate about growth mindset [see earlier discussions here and here] that happened on theconversation.com. Here’s the first salvo by Brooke McNamara, and then the response by Carol Dweck herself. The debate […]
Kevin Lewis sent along this example of what in social science is called the “ecological fallacy”: UNDER EMBARGO UNTIL MARCH 8, 2018 AT 10 AM EST Media Contact: Public and Media Relations Manager Society for Personality and Social Psychology email@example.com Narcolepsy Could Be ‘Sleeper Effect’ in Trump and Brexit Campaigns Regions where voters have more […]
Colleen Flaherty asks: Do you get asked to peer review a lot? I’m guessing you do… This new very short paper says it’s not a crisis, though, since only the people who publish the most are getting asked to review a lot… The authors pose two solutions: either we need to “democratize” the system of […]
The post Mouse Among the Cats appeared first on Statistical Modeling, Causal Inference, and Social Science.
Harry Crane and Ryan Martin write: I’m writing to call your attention to a new peer review and publication platform, called RESEARCHERS.ONE, that I have recently launched with Ryan Martin. The platform can be found at https://www.researchers.one. Given past discussions I’ve seen on your website, I think this new platform might interest you and your […]
Paul Alper writes: Your blog often contains criticisms of articles which get too much publicity. Here is an instance of the obverse (inverse? reverse?) where a worthy publication dealing with a serious medical condition is virtually ignored. From Michael Joyce at the ever-reliable and informative Healthnewsreview.org: Prostate cancer screening: massive study gets minimal coverage. Why? […]
The post What if a big study is done and nobody reports it? appeared first on Statistical Modeling, Causal Inference, and Social Science.
A colleague sent along this article and writes: Check out table 4. this is ERC funded research (the very best of European science get this money). OK, now I was curious, so I scrolled through to table 4. Here it is: Yup, it’s horrible. I don’t know that I’d call it cargo cult science at […]
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There often seems to be an attitude among scientists and journal editors that, if a research team has gone to the trouble of ensuring rigor in some part of their study (whether in the design, the data collection, or the analysis, but typically rigor is associated with “p less than .05” and some random assignment […]
We’re often modeling non-monotonic functions. For example, performance at just about any task increases with age (babies can’t do much!) and then eventually decreases (dead people can’t do much either!). Here’s an example from a few years ago: A function g(x) that increases and then decreases can be modeled by a quadratic, or some more […]
Aki points us to this paper by Tore Selland Kleppe, which begins: Dynamically rescaled Hamiltonian Monte Carlo (DRHMC) is introduced as a computationally fast and easily implemented method for performing full Bayesian analysis in hierarchical statistical models. The method relies on introducing a modified parameterisation so that the re-parameterised target distribution has close to constant […]
Someone who wishes to remain anonymous points to a new study of David Yeager et al. on educational mindset interventions (link from Alex Tabarrok) and asks: On the blog we talk a lot about bad practice and what not to do. Might this be an example of how *to do* things? Or did they just […]
The post The gaps between 1, 2, and 3 are just too large. appeared first on Statistical Modeling, Causal Inference, and Social Science.
I happened to be reading an old issue of Private Eye (a friend subscribes and occasionally gives me some old copies) and came across this, discussing various misinformation regarding a recent crime that had been reported by a London tabloid columnist named Rod Liddle (no relation to the famous statistician, I assume): Here is “what […]
This is the anti-Wolfram. I did not design or write the Stan language. I’m a user of Stan. Lots of people designed and wrote Stan, most notably Bob Carpenter (designed the language and implemented lots of the algorithms), Matt Hoffman (came up with the Nuts algorithm), and Daniel Lee (put together lots of the internals […]
The post Against Winner-Take-All Attribution appeared first on Statistical Modeling, Causal Inference, and Social Science.
For some reason, people have recently been asking me what I think of this journal article which I wrote about months ago . . . so I’ll just repeat my post here: Jordan Anaya pointed me to this post, in which Casper Albers shared this snippet from a recently-published paper from an article in Nature […]
The post “We continuously increased the number of animals until statistical significance was reached to support our conclusions” . . . I think this is not so bad, actually! appeared first on Statistical Modeling, Causal Inference, and Social Science.
Thomas Ball writes: In this article about Nabokov and the influence of John Dunne’s theories on him (and others in the period l’entre deux guerres) you can see intimations of Borges’ story The Garden of Forking Paths…. The article in question is by Nicholson Baker. Nicholson Baker! It’s great to see that he’s still writing. […]
The post Robert Heinlein vs. Lawrence Summers appeared first on Statistical Modeling, Causal Inference, and Social Science.
Not realizing the domain-specificity of their successes.
The post Isaac Newton : Alchemy :: Michael Jordan : Golf appeared first on Statistical Modeling, Causal Inference, and Social Science.
Micah Cohen writes: Our company is establishing a Hall of Fame and I am on a committee to help set it up which involved figuring out the voting system to induct a candidate. We have modeled it somewhat off of the voting for the Baseball Hall of Fame. The details in short: · Up to […]
The post How to set up a voting system for a Hall of Fame appeared first on Statistical Modeling, Causal Inference, and Social Science.
Rob Wilbin writes: I made this quiz where people try to guess ahead of time which results will replicate and which won’t in order to give then a more nuanced understanding of replication issues in psych. Based on this week’s Nature replication paper. It includes quotes and p-values from the original study if people want […]
The post Hey—take this psychological science replication quiz! appeared first on Statistical Modeling, Causal Inference, and Social Science.
Dan Kumprey, a math teacher at Lake Oswego High School, Oregon, writes: Have you considered taking a look at the book Visible Learning by John Hattie? It seems to be permeating and informing reform in our K-12 schools nationwide. Districts are spending a lot of money sending their staffs to conferences by Solution Tree to […]
Max Kasy and Isaiah Andrews sent along this paper, which begins: Some empirical results are more likely to be published than others. Such selective publication leads to biased estimates and distorted inference. This paper proposes two approaches for identifying the conditional probability of publication as a function of a study’s results, the first based on […]
The post “Identification of and correction for publication bias,” and another discussion of how forking paths is not the same thing as file drawer appeared first on Statistical Modeling, Causal Inference, and Social Science.
I’ve been doing some flying, which gives me the opportunity to see various movies on that little seat-back screen. And some of these movies have been pretty good: Logan Lucky. Pure 70s. Kinda like how Stravinsky did those remakes of Tchaikovsky etc. that were cleaner than the original, so did Soderbergh in Logan Lucky, and […]
The post 3 recent movies from the 50s and the 70s appeared first on Statistical Modeling, Causal Inference, and Social Science.