Posts Tagged ‘ Causal Inference ’

We’re hiring! hiring! hiring! hiring!

January 17, 2017
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[insert picture of adorable cat entwined with Stan logo] We’re hiring postdocs to do Bayesian inference. We’re hiring programmers for Stan. We’re hiring a project manager. How many people we hire depends on what gets funded. But we’re hiring a few people for sure. We want the best best people who love to collaborate, who […] The post We’re hiring! hiring! hiring! hiring! appeared first on Statistical Modeling, Causal Inference,…

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No evidence of incumbency disadvantage?

January 14, 2017
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No evidence of incumbency disadvantage?

Several years ago I learned that the incumbency advantage in India was negative! There, the politicians are so unpopular that when they run for reelection they’re actually at a disadvantage, on average, compared to fresh candidates. At least, that’s what I heard. But Andy Hall and Anthony Fowler just wrote a paper claiming that, no, […] The post No evidence of incumbency disadvantage? appeared first on Statistical Modeling, Causal Inference,…

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Problems with “incremental validity” or more generally in interpreting more than one regression coefficient at a time

January 13, 2017
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Problems with “incremental validity” or more generally in interpreting more than one regression coefficient at a time

Kevin Lewis points us to this interesting paper by Jacob Westfall and Tal Yarkoni entitled, “Statistically Controlling for Confounding Constructs Is Harder than You Think.” Westfall and Yarkoni write: A common goal of statistical analysis in the social sciences is to draw inferences about the relative contributions of different variables to some outcome variable. When […] The post Problems with “incremental validity” or more generally in interpreting more than one…

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Problems with randomized controlled trials (or any bounded statistical analysis) and thinking more seriously about story time

January 10, 2017
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In 2010, I wrote: As a statistician, I was trained to think of randomized experimentation as representing the gold standard of knowledge in the social sciences, and, despite having seen occasional arguments to the contrary, I still hold that view, expressed pithily by Box, Hunter, and Hunter (1978) that “To find out what happens when […] The post Problems with randomized controlled trials (or any bounded statistical analysis) and thinking…

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Field Experiments and Their Critics

January 3, 2017
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Seven years ago I was contacted by Dawn Teele, who was then a graduate student and is now a professor of political science, and asked for my comments on an edited book she was preparing on social science experiments and their critics. I responded as follows: This is a great idea for a project. My […] The post Field Experiments and Their Critics appeared first on Statistical Modeling, Causal Inference,…

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About that claim in the Monkey Cage that North Korea had “moderate” electoral integrity . . .

January 3, 2017
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Yesterday I wrote about problems with the Electoral Integrity Project, a set of expert surveys that are intended to “evaluate the state of the world’s elections” but have some problems, notably rating more than half of the U.S. states in 2016 as having lower integrity than Cuba (!) and North Korea (!!!) in 2014. I […] The post About that claim in the Monkey Cage that North Korea had “moderate”…

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Transformative treatments

December 31, 2016
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Transformative treatments

Kieran Healy and Laurie Paul wrote a new article, “Transformative Treatments,” (see also here) which reminds me a bit of my article with Guido, “Why ask why? Forward causal inference and reverse causal questions.” Healy and Paul’s article begins: Contemporary social-scientific research seeks to identify specific causal mechanisms for outcomes of theoretical interest. Experiments that […] The post Transformative treatments appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Sorry, but no, you can’t learn causality by looking at the third moment of regression residuals

December 28, 2016
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Under the subject line “Legit?”, Kevin Lewis pointed me to this press release, “New statistical approach will help researchers better determine cause-effect.” I responded, “No link to any of the research papers, so cannot evaluate.” In writing this post I thought I’d go further. The press release mentions 6 published articles so I googled the […] The post Sorry, but no, you can’t learn causality by looking at the third…

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You’ll have to figure this one out for yourselves.

December 21, 2016
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You’ll have to figure this one out for yourselves.

So. The other day this following email comes in, subject line “Grabbing headlines using poor statistical methods,” from Clifford Anderson-Bergman: Here’s another to file under “How to get mainstream publication by butchering your statistics”. The paper: Comparison of Hospital Mortality and Readmission Rates for Medicare Patients Treated by Male vs Female Physicians Journal: JAMA Featured […] The post You’ll have to figure this one out for yourselves. appeared first on…

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You’ll have to figure this one out for yourselves.

December 21, 2016
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You’ll have to figure this one out for yourselves.

So. The other day this following email comes in, subject line “Grabbing headlines using poor statistical methods,” from Clifford Anderson-Bergman: Here’s another to file under “How to get mainstream publication by butchering your statistics”. The paper: Comparison of Hospital Mortality and Readmission Rates for Medicare Patients Treated by Male vs Female Physicians Journal: JAMA Featured […] The post You’ll have to figure this one out for yourselves. appeared first on…

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