Posts Tagged ‘ Causal Inference ’

My talk at MIT this Thursday

May 13, 2015
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When I was a student at MIT, there was no statistics department. I took a statistics course from Stephan Morgenthaler and liked it. (I’d already taken probability and stochastic processes back at the University of Maryland; my instructor in the latter class was Prof. Grace Yang, who was super-nice. I couldn’t follow half of what […] The post My talk at MIT this Thursday appeared first on Statistical Modeling, Causal…

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What I got wrong (and right) about econometrics and unbiasedness

May 8, 2015
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Yesterday I spoke at the Princeton economics department. The title of my talk was: “Unbiasedness”: You keep using that word. I do not think it means what you think it means. The talk went all right—people seemed ok with what I was saying—but I didn’t see a lot of audience involvement. It was a bit […] The post What I got wrong (and right) about econometrics and unbiasedness appeared first…

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A causal-inference version of a statistics problem: If you fit a regression model with interactions, and the underlying process has an interaction, your coefficients won’t be directly interpretable

May 4, 2015
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A causal-inference version of a statistics problem:  If you fit a regression model with interactions, and the underlying process has an interaction, your coefficients won’t be directly interpretable

A colleague pointed me to a recent paper, “Does Regression Produce Representative Estimates of Causal Effects?” by Peter Aronow and Cyrus Samii, which begins: With an unrepresentative sample, the estimate of a causal effect may fail to characterize how effects operate in the population of interest. What is less well understood is that conventional estimation […] The post A causal-inference version of a statistics problem: If you fit a regression…

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This year’s Atlantic Causal Inference Conference: 20-21 May

April 26, 2015
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Dylan Small writes: The conference will take place May 20-21 (with a short course on May 19th) and the web site for the conference is here. The deadline for submitting a poster title for the poster session is this Friday. Junior researchers (graduate students, postdoctoral fellows, and assistant professors) whose poster demonstrates exceptional research will […] The post This year’s Atlantic Causal Inference Conference: 20-21 May appeared first on Statistical…

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“Thinking about the possibility of spurious correlation isn’t a matter of liking—it should be pretty much automatic.”

April 4, 2015
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I agree with sociologist David Weakliem when he writes the above sentence. Here’s the full paragraph: Krugman says, “you can, if you like, try to argue that this relationship is spurious, maybe not causal.” Actually, I [Weakliem] liked his original figure, since I agree with Krugman on economic policy. But thinking about the possibility of […] The post “Thinking about the possibility of spurious correlation isn’t a matter of liking—it…

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Time-release pedagogy??

March 31, 2015
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Time-release pedagogy??

Mark Palko points to this report and writes: Putting aside my concerns with the “additional years of learning” metric (and I have a lot of them), I have the feeling that there’s something strange here or i’m missing something obvious. That jump from 3-year impact to 4-year seems excessive. The press release links to a […] The post Time-release pedagogy?? appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Bayesian models, causal inference, and time-varying exposures

March 20, 2015
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Mollie Wood writes: I am a doctoral student in clinical and population health research. My dissertation research is on prenatal medication exposure and neurodevelopmental outcomes in children, and I’ve encountered a difficult problem that I hope you might be able to advise me on. I am working on a problem in which my main exposure […] The post Bayesian models, causal inference, and time-varying exposures appeared first on Statistical Modeling,…

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The State of the Art in Causal Inference: Some Changes Since 1972

March 16, 2015
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For the first issue of the journal Observational Studies, editor Dylan Small will reprint William Cochran’s 1972 article on the topic (which begins, “Observational studies are a class of statistical studies that have increased in frequency and importance during the past 20 years. In an observational study the investigator is restricted to taking selected observations […] The post The State of the Art in Causal Inference: Some Changes Since 1972…

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Stock-and-flow and other concepts that are important in statistical modeling but typically don’t get taught to statisticians

March 12, 2015
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Bill Harris writes: You’ve written about causality somewhat often, and you, along with perhaps everyone who has done anything with statistics, have written that “correlation is not causation.” When you say that correlation is not causation, you seem to be pointing out cases where correlation exists but causality does not. While that’s important, there’s another […] The post Stock-and-flow and other concepts that are important in statistical modeling but typically…

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Causal Impact from Google

March 8, 2015
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Bill Harris writes: Did you see http://blog.revolutionanalytics.com/2014/09/google-uses-r-to-calculate-roi-on-advertising-campaigns.html? Would that be something worth a joint post and discussion from you and Judea? I then wrote: Interesting. It seems to all depend on the choice of “control time series.” That said, it could still be a useful method. Bill replied: The good: Bayesian approaches made very approachable […] The post Causal Impact from Google appeared first on Statistical Modeling, Causal Inference, and…

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