Posts Tagged ‘ Causal Inference ’

Fitting multilevel models when predictors and group effects correlate

November 12, 2017
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Ryan Bain writes: I came across your ‘Fitting Multilevel Models When Predictors and Group Effects Correlate‘ paper that you co-authored with Dr. Bafumi and read it with great interest. I am a current postgraduate student at the University of Glasgow writing a dissertation examining explanations of Euroscepticism at the individual and country level since the […] The post Fitting multilevel models when predictors and group effects correlate appeared first on…

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Why you can’t simply estimate the hot hand using regression

November 6, 2017
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Jacob Schumaker writes: Reformed political scientist, now software engineer here. Re: the hot hand fallacy fallacy from Miller and Sanjurjo, has anyone discussed why a basic regression doesn’t solve this? If they have I haven’t seen it. The idea is just that there are other ways of measuring the hot hand. When I think of […] The post Why you can’t simply estimate the hot hand using regression appeared first…

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

October 23, 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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Workshop on Interpretable Machine Learning

October 11, 2017
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Andrew Gordon Wilson sends along this conference announcement: NIPS 2017 Symposium Interpretable Machine Learning Long Beach, California, USA December 7, 2017 Call for Papers: We invite researchers to submit their recent work on interpretable machine learning from a wide range of approaches, including (1) methods that are designed to be more interpretable from the start, […] The post Workshop on Interpretable Machine Learning appeared first on Statistical Modeling, Causal Inference,…

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What am I missing and what will this paper likely lead researchers to think and do?

October 5, 2017
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This post is by Keith. In a previous post Ken Rice brought our attention to a recent paper he had published with Julian Higgins and  Thomas Lumley (RHL). After I obtained access and read the paper, I made some critical comments regarding RHL which ended with “Or maybe I missed something.” This post will try to discern […] The post What am I missing and what will this paper likely lead researchers…

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“From ‘What If?’ To ‘What Next?’ : Causal Inference and Machine Learning for Intelligent Decision Making”

October 2, 2017
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Panos Toulis writes in to announce this conference: NIPS 2017 Workshop on Causal Inference and Machine Learning (WhatIF2017) “From ‘What If?’ To ‘What Next?’ : Causal Inference and Machine Learning for Intelligent Decision Making” — December 8th 2017, Long Beach, USA. Submission deadline for abstracts and papers: October 31, 2017 Acceptance decisions: November 7, 2017 […] The post “From ‘What If?’ To ‘What Next?’ : Causal Inference and Machine Learning…

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Air rage update

September 22, 2017
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So. Marcus Crede, Carol Nickerson, and I published a letter in PPNAS criticizing the notorious “air rage” article. (Due to space limitations, our letter contained only a small subset of the many possible criticisms of that paper.) Our letter was called “Questionable association between front boarding and air rage.” The authors of the original paper, […] The post Air rage update appeared first on Statistical Modeling, Causal Inference, and Social…

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Causal inference using data from a non-representative sample

September 14, 2017
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Dan Gibbons writes: I have been looking at using synthetic control estimates for estimating the effects of healthcare policies, particularly because for say county-level data the nontreated comparison units one would use in say a difference-in-differences estimator or quantile DID estimator (if one didn’t want to use the mean) are not especially clear. However, given […] The post Causal inference using data from a non-representative sample appeared first on Statistical…

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“How conditioning on post-treatment variables can ruin your experiment and what to do about it”

September 12, 2017
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“How conditioning on post-treatment variables can ruin your experiment and what to do about it”

Brendan Nyhan writes: Thought this might be of interest – new paper with Jacob Montgomery and Michelle Torres, How conditioning on post-treatment variables can ruin your experiment and what to do about it. The post-treatment bias from dropout on Turk you just posted about is actually in my opinion a less severe problem than inadvertent […] The post “How conditioning on post-treatment variables can ruin your experiment and what to…

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Rosenbaum (1999): Choice as an Alternative to Control in Observational Studies

September 4, 2017
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Winston Lin wrote in a blog comment earlier this year: Paul Rosenbaum’s 1999 paper “Choice as an Alternative to Control in Observational Studies” is really thoughtful and well-written. The comments and rejoinder include an interesting exchange between Manski and Rosenbaum on external validity and the role of theories. And here it is. Rosenbaum begins: In […] The post Rosenbaum (1999): Choice as an Alternative to Control in Observational Studies appeared…

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