Posts Tagged ‘ Causal Inference ’

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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Six quick tips to improve your regression modeling

January 29, 2015
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It’s Appendix A of ARM: A.1. Fit many models Think of a series of models, starting with the too-simple and continuing through to the hopelessly messy. Generally it’s a good idea to start simple. Or start complex if you’d like, but prepare to quickly drop things out and move to the simpler model to help […] The post Six quick tips to improve your regression modeling appeared first on Statistical…

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A bunch of papers

January 20, 2015
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A bunch of papers

The beginning of the new year has been particularly busy, as I'm working on several interesting projects. On the bright side, some of these are starting to give their fruits and, coincidentally, in the last few days we've had a few papers finalise...

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“Epidemiology and Biostatistics: competitive or complementary?”

January 11, 2015
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Mohammad Mansournia writes: I have a 20 minute lecture on “Epidemiology and Biostatistics: competitive or complementary?” at Tehran University of Medical Sciences in the next month. I should mention the difference between an epidemiologist and a biostatistician and their competitive or complementary roles in public health. I am wondering if you have any thoughts on […] The post “Epidemiology and Biostatistics: competitive or complementary?” appeared first on Statistical Modeling, Causal…

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Designing a study to see if “the 10x programmer” is a real thing

December 4, 2014
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Lorin H. writes: One big question in the world of software engineering is: how much variation is there in productivity across programmers? (If you google for “10x programmer” you’ll see lots of hits). Let’s say I wanted to explore this research question with a simple study. Choose a set of participants at random from a […] The post Designing a study to see if “the 10x programmer” is a real…

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If observational studies are outlawed, then only outlaws will do observational studies

December 3, 2014
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If observational studies are outlawed, then only outlaws will do observational studies

My article “Experimental reasoning in social science” begins as follows: 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 […] The post If observational studies are outlawed, then only outlaws will do observational studies…

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Retrospective clinical trials?

November 20, 2014
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Kelvin Leshabari writes: I am a young medical doctor in Africa who wondered if it is possible to have a retrospective designed randomised clinical trial and yet be sound valid in statistical sense. This is because to the best of my knowledge, the assumptions underlying RCT methodology include that data is obtained in a prospective […] The post Retrospective clinical trials? appeared first on Statistical Modeling, Causal Inference, and Social…

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