Posts Tagged ‘ Causal Inference ’

Is Rigor Contagious? (my talk next Monday 4:15pm at Columbia)

February 24, 2017
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Is Rigor Contagious? Much of the theory and practice of statistics and econometrics is characterized by a toxic mixture of rigor and sloppiness. Methods are justified based on seemingly pure principles that can’t survive reality. Examples of these principles include random sampling, unbiased estimation, hypothesis testing, Bayesian inference, and causal identification. Examples of uncomfortable reality […] The post Is Rigor Contagious? (my talk next Monday 4:15pm at Columbia) appeared first…

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Cloak and dagger

February 22, 2017
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Cloak and dagger

Elan B. writes: I saw this JAMA Pediatrics article [by Julia Raifman, Ellen Moscoe, and S. Bryn Austin] getting a lot of press for claiming that LGBT suicide attempts went down 14% after gay marriage was legalized. The heart of the study is comparing suicide attempt rates (in last 12 months) before and after exposure — gay marriage legalization […] The post Cloak and dagger appeared first on Statistical Modeling, Causal Inference, and Social…

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Cloak and dagger

February 22, 2017
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Cloak and dagger

Elan B. writes: I saw this JAMA Pediatrics article [by Julia Raifman, Ellen Moscoe, and S. Bryn Austin] getting a lot of press for claiming that LGBT suicide attempts went down 14% after gay marriage was legalized. The heart of the study is comparing suicide attempt rates (in last 12 months) before and after exposure — gay marriage legalization […] The post Cloak and dagger appeared first on Statistical Modeling, Causal Inference, and Social…

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Looking for rigor in all the wrong places (my talk this Thursday in the Columbia economics department)

February 21, 2017
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Looking for rigor in all the wrong places (my talk this Thursday in the Columbia economics department)

Looking for Rigor in All the Wrong Places What do the following ideas and practices have in common: unbiased estimation, statistical significance, insistence on random sampling, and avoidance of prior information? All have been embraced as ways of enforcing rigor but all have backfired and led to sloppy analyses and erroneous inferences. We discuss these […] The post Looking for rigor in all the wrong places (my talk this Thursday…

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Vine regression?

February 17, 2017
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Jeremy Neufeld writes: I’m an undergraduate student at the University of Maryland and I was recently referred to this paper (Vine Regression, by Roger Cooke, Harry Joe, and Bo Chang), also an accompanying summary blog post by the main author) as potentially useful in policy analysis. With the big claims it makes, I am not […] The post Vine regression? appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Storytelling as predictive model checking

February 10, 2017
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Storytelling as predictive model checking

I finally got around to reading Adam Begley’s biography of John Updike, and it was excellent. I’ll have more on that in a future post, but for now I just went to share the point, which I’d not known before, that almost all of Updike’s characters and even the descriptions and events in many of […] The post Storytelling as predictive model checking appeared first on Statistical Modeling, Causal Inference,…

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When do protests affect policy?

February 1, 2017
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When do protests affect policy?

Gur Huberman writes that he’s been wondering for many years about this question: One function of protests is to vent out the protesters’ emotions. When do protests affect policy? In dictatorships there are clear examples of protests affecting reality, e.g., in Eastern Europe in 1989. It’s harder to find such clear examples in democracies. And […] The post When do protests affect policy? appeared first on Statistical Modeling, Causal Inference,…

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Face value

January 23, 2017
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This is actually a not-so-recent paper, but I've only discovered now and I think it's very interesting. The underlying issue is about trying to do "causal inference" from observational data $-$ perhaps one could see this in a simpler way by considering...

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Quantifying uncertainty in identification assumptions—this is important!

January 22, 2017
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Quantifying uncertainty in identification assumptions—this is important!

Luis Guirola writes: I’m a poli sci student currently working on methods. I’ve seen you sometimes address questions in your blog, so here is one in case you wanted. I recently read some of Chuck Manski book “Identification for decision and prediction”. I take his main message to be “The only way to get identification […] The post Quantifying uncertainty in identification assumptions—this is important! appeared first on Statistical Modeling,…

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Come and work with us!

January 18, 2017
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Stan is an open-source, state-of-the-art probabilistic programming language with a high-performance Bayesian inference engine written in C++. Stan had been successfully applied to modeling problems with hundreds of thousands of parameters in fields as diverse as econometrics, sports analytics, physics, pharmacometrics, recommender systems, political science, and many more. Research using Stan has been featured in […] The post Come and work with us! appeared first on Statistical Modeling, Causal Inference,…

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