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 […]
It has been just a few months since I reviewed five free and open-source point-and-click graphical user interfaces (GUIs) to the R language. I plan to keep those reviews up to date as new features are added. BlueSky’s interface would … Continue reading →
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 […]
The post Bob Erikson on the 2018 Midterms appeared first on Statistical Modeling, Causal Inference, and Social Science.
The Johns Hopkins Data Science Lab has been teaching massive online open courses for more than 5 years now. During that time we’ve reached more than 5 million learners who want to break into the number one rated job in America.
While we have bee…
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 […]
Where you are in the Journey* Cox: [I]n some ﬁelds foundations do not seem very important, but we both think that foundations of statistical inference are important; why do you think that is? Mayo: I think because they ask about fundamental questions of evidence, inference, and probability … we invariably cross into philosophical questions about […]
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 […]
The post “Imaginary gardens with real data” appeared first on Statistical Modeling, Causal Inference, and Social Science.
Rolando Acosta and I recently posted a manuscript on bioRxiv describing the effects of Hurricane María, based on an analysis of mortality data provided by the Demographic Registry. I was also an author on a paper published in May based on a survey of 3…
Very cool project and possibility to work 3 years developing Stan and collaborating with me (Aki) and other Stan development team. Deadline for applications is 22 October. Quantitative Modelling of Cell Metabolism (QMCM) group headed by Professor Lars Keld Nielsen at DTU, Copenhagen, is looking for experienced Bayesian statistician for a postdoc position. Group specializes […]
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.
Sri Lanka has a rapidly growing tourism industry, two international tourism seasons, and seasonality patterns in arrivals that vary according to country of origin.
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.
Error Statistics Philosophy: Blog Contents (7 years) [i] By: D. G. Mayo Dear Reader: I began this blog 7 years ago (Sept. 3, 2011)! A big celebration is taking place at the Elbar Room this evening, both for the blog and the appearance of my new book: Statistical Inference as Severe Testing: How to Get Beyond the […]