Category: Statistics

“Six Signs of Scientism”: where I disagree with Haack

I came across this article, “Six Signs of Scientism,” by philosopher Susan Haack from 2009. I think I’m in general agreement with Haack’s views—science has made amazing progress over the centuries but “like all human enterprises, science is ineradicably is fallible and imperfect. At best its progress is ragged, uneven, and unpredictable; moreover, much scientific […]

The post “Six Signs of Scientism”: where I disagree with Haack appeared first on Statistical Modeling, Causal Inference, and Social Science.

David Weakliem points out that both economic and cultural issues can be more or less “moralized.”

David Weakliem writes: Thomas Edsall has a piece in which he cites a variety of work saying that Democratic and Republican voters are increasingly divided by values. He’s particularly concerned with “authoritarianism,” which is an interesting issue, but one I’ll save for another post. What I want to talk about here is the idea that […]

The post David Weakliem points out that both economic and cultural issues can be more or less “moralized.” appeared first on Statistical Modeling, Causal Inference, and Social Science.

“Moral cowardice requires choice and action.”

Commenter Chris G pointed out this quote from Ta-Nehisi Coates: Moral cowardice requires choice and action. It demands that its adherents repeatedly look away, that they favor the fanciful over the plain, myth over history, the dream over the real. Coates was writing about the defenders of the Confederate flag. Coates points to this quotation […]

The post “Moral cowardice requires choice and action.” appeared first on Statistical Modeling, Causal Inference, and Social Science.

Cool postdoc position in Arizona on forestry forecasting using tree ring models!

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 post Cool postdoc position in Arizona on forestry forecasting using tree ring models! appeared first on Statistical Modeling, Causal Inference, and Social Science.

My talk tomorrow (Tues) 4pm in the Biomedical Informatics department (at 168th St)

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 […]

The post My talk tomorrow (Tues) 4pm in the Biomedical Informatics department (at 168th St) appeared first on Statistical Modeling, Causal Inference, and Social Science.

Bob Erikson on the 2018 Midterms

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.

What do you do when someone says, “The quote is, this is the exact quote”—and then misquotes you?

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 […]

The post What do you do when someone says, “The quote is, this is the exact quote”—and then misquotes you? appeared first on Statistical Modeling, Causal Inference, and Social Science.

Excursion 2: Taboos of Induction and Falsification: Tour I (first stop)

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 […]

Statistical Modeling, Causal Inference, and Social Science Regrets Its Decision to Hire Cannibal P-hacker as Writer-at-Large

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.

“Imaginary gardens with real data”

“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.

Postdoc position: Stan and composite mechanistic and data-driven models of cellular metabolism

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 […]

The post Postdoc position: Stan and composite mechanistic and data-driven models of cellular metabolism appeared first on Statistical Modeling, Causal Inference, and Social Science.

(People are missing the point on Wansink, so) what’s the lesson we should be drawing from this story?

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 […]

The post (People are missing the point on Wansink, so) what’s the lesson we should be drawing from this story? appeared first on Statistical Modeling, Causal Inference, and Social Science.

Using Stacking to Average Bayesian Predictive Distributions (with Discussion)

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 […]

The post Using Stacking to Average Bayesian Predictive Distributions (with Discussion) appeared first on Statistical Modeling, Causal Inference, and Social Science.

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

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.

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.”

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.

You’ve got data on 35 countries, but it’s really just N=3 groups.

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. […]

The post You’ve got data on 35 countries, but it’s really just N=3 groups. appeared first on Statistical Modeling, Causal Inference, and Social Science.