Margaret Evans sends in this cool job ad: Two-Year Post Doctoral Fellowship in Forest Ecological Forecasting, Data Assimilation A post-doctoral fellowship is available in the Laboratory of Tree-Ring Research (University of Arizona) to work on an NSF Macrosystems Biology-funded project assimilating together tree-ring and forest inventory data to analyze patterns and drivers of forest productivity […]
The talk is 4-5pm in Room 200 on the 20th floor of the Presbyterian Hospital Building, Columbia University Medical Center. I’m not sure what I’m gonna talk about. It’ll depend on what people are interested in discussing. Here are some possible topics: – The failure of null hypothesis significance testing when studying incremental changes, and […]
A couple months ago I wrote about party balancing in the midterm elections and pointed to the work of Joe Bafumi, Bob Erikson, and Chris Wlezien. Erikson recently sent me this note on the upcoming midterm elections: Donald Trump’s tumultuous presidency has sparked far more than the usual interest in the next midterm elections as […]
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Ezra Klein, editor of the news/opinion website Vox, reports on a recent debate that sits in the center of the Venn diagram of science, journalism, and politics: Sam Harris, host of the Waking Up podcast, and I [Klein] have been going back and forth over an interview Harris did with The Bell Curve author Charles […]
It is not easy to admit our mistakes, particularly now, given the current media climate and general culture of intolerance on college campuses. Still, we feel that we owe our readers an apology. We should not have hired Cannibal P-hacker, an elegant scientist and thinker who, we have come to believe, after serious consideration, does […]
The post Statistical Modeling, Causal Inference, and Social Science Regrets Its Decision to Hire Cannibal P-hacker as Writer-at-Large appeared first on Statistical Modeling, Causal Inference, and Social Science.
“Statistics” by Marianne Moore, almost I, too, dislike it: there are things that are important beyond all this fiddle. Reading it, however, with a perfect contempt for it, one discovers that there is in it after all, a place for the genuine. Hands that can grasp, eyes that can dilate, hair that can rise if […]
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People pointed me to various recent news articles on the retirement from the Cornell University business school of eating-behavior researcher and retraction king Brian Wansink. I particularly liked this article by David Randall—not because he quoted me, but because he crisply laid out the key issues: The irreproducibility crisis cost Brian Wansink his job. Over […]
I’ve posted on this paper (by Yuling Yao, Aki Vehtari, Daniel Simpson, and myself) before, but now the final version has been published, along with a bunch of interesting discussions and our rejoinder. This has been an important project for me, as it answers a question that’s been bugging me for over 20 years (since […]
In econometrics, or applied economics, a “placebo test” is not a comparison of a drug to a sugar pill. Rather, it’s a sort of conceptual placebo, in which you repeat your analysis using a different dataset, or a different part of your dataset, where no intervention occurred. For example, if you’re performing some analysis studying […]
The post A potential big problem with placebo tests in econometrics: they’re subject to the “difference between significant and non-significant is not itself statistically significant” issue appeared first on Statistical Modeling, Causal Inference, and Social Science.
This sounds super interesting: Vacancy Information: Mathematical Statistician, GS-1529-14 Please apply at one of the following: · DE (External candidates to the US GOV) Announcement: HHS-CDC-D3-18-10312897 · MP (Internal candidates to the US GOV) Announcement: HHS-CDC-M3-18-10312898 Location: Atlanta, GA – Centers for Disease Control and Prevention – National Center for Immunization and Respiratory Disease – […]
The post Job opening at CDC: “The Statistician will play a central role in guiding the statistical methods of all major projects of the Epidemiology and Prevention Branch of the CDC Influenza Division, and aid in designing, analyzing, and interpreting research intended to understand the burden of influenza in the US and internationally and identify the best influenza vaccines and vaccine strategies.” appeared first on Statistical Modeling, Causal Inference, and Social Science.
Jon Baron points to a recent article, “Societal inequalities amplify gender gaps in math,” by Thomas Breda, Elyès Jouini, and Clotilde Napp (supplementary materials here), and writes: A particular issue bothers me whenever I read studies like this, which use nations as the unit of analysis and then make some inference from correlations across nations. […]
Aleksi Reito writes: The statement below was included in a recent issue of Annals of Surgery: But, as 80% power is difficult to achieve in surgical studies, we argue that the CONSORT and STROBE guidelines should be modified to include the disclosure of power—even if less than 80%—with the given sample size and effect size […]
In her recent article about pizzagate, Stephanie Lee included this hilarious email from Brian Wansink, the self-styled “world-renowned eating behavior expert for over 25 years”: OK, what grabs your attention is that last bit about “tweeking” the data to manipulate the p-value, where Wansink is proposing research misconduct (from NIH: “Falsification: Manipulating research materials, equipment, […]
The post “Tweeking”: The big problem is not where you think it is. appeared first on Statistical Modeling, Causal Inference, and Social Science.
[image of cat lifting weights] A graduate student who wishes to remain anonymous writes: I was wondering if you could answer an elementary question which came to mind after reading your article with Carlin on retrospective power analysis. Consider the field of exercise science, and in particular studies on people who lift weights. (I sometimes […]
Under the heading, “An example of Stan to the rescue, multiverse analysis, and psychologists trying to do well,” Greg Cox writes: I’m currently a postdoc at Syracuse University studying how human memory works. I wanted to forward a paper of ours [“Information and Processes Underlying Semantic and Episodic Memory Across Tasks, Items, and Individuals,” by […]
This came up in response to a student’s question. I wrote that, in general, you can plot a function y(x) on a simple graph. You can plot y(x,x2) by plotting y vs x and then having several lines showing different values of x2 (for example, x2=0, x2=0.5, x2=1, x2=1.5, x2=2, etc). You can plot y(x,x2,x3,x4) […]
The post How to graph a function of 4 variables using a grid appeared first on Statistical Modeling, Causal Inference, and Social Science.
Gabriel Power writes: I don’t recall that you addressed this point in your posts on post-publication peer review [for example, here and here — ed.]. Who would be allowed to post reviews of a paper? Anyone? Only researchers? Only experts? Science is not a democracy. A study is not valid because a majority of people […]
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Back in 2013, I wrote a post regarding a controversial claim that high genetic diversity, or low genetic diversity, is bad for the economy: Two economics professors, Quamrul Ashraf and Oded Galor, wrote a paper, “The Out of Africa Hypothesis, Human Genetic Diversity, and Comparative Economic Development,” that is scheduled to appear in the American […]
The post A couple more papers on genetic diversity as an explanation for why Africa and remote Andean countries are so poor while Europe and North America are so wealthy appeared first on Statistical Modeling, Causal Inference, and Social Science.
Roland Langrock writes: Since on your blog you’ve regularly been discussing hot hand literature – which we closely followed – I’m writing to share with you a new working paper we wrote on a potential hot hand pattern in professional darts. We use state-space models in which a continuous-valued latent “hotness” variable, modeled as an […]
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Matthew Poes writes: I’m writing a research memo discussing the importance of precisely aligning the outcome measures to the intervention activities. I’m making the point that an evaluation of the outcomes for a given intervention may net null results for many reasons, one of which could simply be that you are looking in the wrong […]