Posts Tagged ‘ Causal Inference ’

How does a Nobel-prize-winning economist become a victim of bog-standard selection bias?

July 20, 2017
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Someone who wishes to remain anonymous writes in with a story: Linking to a new paper by Jorge Luis García, James J. Heckman, and Anna L. Ziff, an economist Sue Dynarski makes this “joke” on facebook—or maybe it’s not a joke: How does one adjust standard errors to account for the fact that N of […] The post How does a Nobel-prize-winning economist become a victim of bog-standard selection bias?…

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His concern is that the authors don’t control for the position of games within a season.

July 19, 2017
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Chris Glynn wrote last year: I read your blog post about middle brow literature and PPNAS the other day. Today, a friend forwarded me this article in The Atlantic that (in my opinion) is another example of what you’ve recently been talking about. The research in question is focused on Major League Baseball and the […] The post His concern is that the authors don’t control for the position of…

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How to design future studies of systemic exercise intolerance disease (chronic fatigue syndrome)?

July 17, 2017
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Someone named Ramsey writes on behalf of a self-managed support community of 100+ systemic exercise intolerance disease (SEID) patients. He read my recent article on the topic and had a question regarding the following excerpt: For conditions like S.E.I.D., then, the better approach may be to gather data from people suffering “in the wild,” combining […] The post How to design future studies of systemic exercise intolerance disease (chronic fatigue…

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Statisticians and economists agree: We should learn from data by “generating and revising models, hypotheses, and data analyzed in response to surprising findings.” (That’s what Bayesian data analysis is all about.)

July 6, 2017
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Kevin Lewis points us to this article by economist James Heckman and statistician Burton Singer, who write: All analysts approach data with preconceptions. The data never speak for themselves. Sometimes preconceptions are encoded in precise models. Sometimes they are just intuitions that analysts seek to confirm and solidify. A central question is how to revise […] The post Statisticians and economists agree: We should learn from data by “generating and…

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Analyze all your comparisons. That’s better than looking at the max difference and trying to do a multiple comparisons correction.

June 25, 2017
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Analyze all your comparisons.  That’s better than looking at the max difference and trying to do a multiple comparisons correction.

[cat picture] The following email came in: I’m in a PhD program (poli sci) with a heavy emphasis on methods. One thing that my statistics courses emphasize, but that doesn’t get much attention in my poli sci courses, is the problem of simultaneous inferences. This strikes me as a problem. I am a bit unclear […] The post Analyze all your comparisons. That’s better than looking at the max difference…

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The Publicity Factory: How even serious research gets exaggerated by the process of scientific publication and media exposure

June 6, 2017
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The starting point is that we’ve seen a lot of talk about frivolous science, headline-bait such as the study that said that married women are more likely to vote for Mitt Romney when ovulating, or the study that said that girl-named hurricanes are more deadly than boy-named hurricanes, and at this point some of these […] The post The Publicity Factory: How even serious research gets exaggerated by the process…

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The Other Side of the Night

May 24, 2017
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The Other Side of the Night

Don Green points us to this quantitative/qualitative meta-analysis he did with Betsy Levy Paluck and Seth Green. The paper begins: This paper evaluates the state of contact hypothesis research from a policy perspective. Building on Pettigrew and Tropp’s (2006) influential meta-analysis, we assemble all intergroup contact studies that feature random assignment and delayed outcome measures, […] The post The Other Side of the Night appeared first on Statistical Modeling, Causal…

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Causal inference using Bayesian additive regression trees: some questions and answers

May 18, 2017
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[cat picture] Rachael Meager writes: We’re working on a policy analysis project. Last year we spoke about individual treatment effects, which is the direction we want to go in. At the time you suggested BART [Bayesian additive regression trees; these are not averages of tree models as are usually set up; rather, the key is […] The post Causal inference using Bayesian additive regression trees: some questions and answers appeared…

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Danger Sign

May 1, 2017
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Melvyn Weeks writes: I [Weeks] have a question related to comparability and departures thereof in regression models. I am familiar with these issues, namely the problems of a lack of complete overlap and imbalance as applied to treatment models where there exists a binary treatment. However, it strikes me that these issues apply more generally […] The post Danger Sign appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Workshop on The Regression Discontinuity Design

April 18, 2017
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Workshop on The Regression Discontinuity Design

As part of our bid to get an MRC grant (which we managed to do), we promised that, if successful, we'd also have a dissemination workshop, at the end of the project. Well, the project on the Regression Discontinuity Design (RDD) has now finished f...

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