Skip to content
Archive of posts filed under the Causal Inference category.

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

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 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, […]

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

[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 […]

Danger Sign

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 […]

Causal inference conference in North Carolina

[cat picture] Michael Hudgens announces: Registration for the 2017 Atlantic Causal Inference Conference is now open. The registration site is here. More information about the conference, including the poster session and the Second Annual Causal Inference Data Analysis Challenge can be found on the conference website here. We held the very first Atlantic Causal Inference Conference here […]

Causal inference conference at Columbia University on Sat 6 May: Varying Treatment Effects

Hey! We’re throwing a conference: Varying Treatment Effects The literature on causal inference focuses on estimating average effects, but the very notion of an “average effect” acknowledges variation. Relevant buzzwords are treatment interactions, situational effects, and personalized medicine. In this one-day conference we shall focus on varying effects in social science and policy research, with […]

Let’s accept the idea that treatment effects vary—not as something special but just as a matter of course

Tyler Cowen writes: Does knowing the price lower your enjoyment of goods and services? I [Cowen] don’t quite agree with this as stated, as the experience of enjoying a bargain can make it more pleasurable, or at least I have seen this for many people. Some in fact enjoy the bargain only, not the actual […]

This could be a big deal: the overuse of psychotropic medications for advanced Alzheimer’s patients

I received the following email, entitled “A research lead (potentially bigger than the opioid epidemic,” from someone who wishes to remain anonymous: My research lead is related to the use of psychotropic medications in Alzheimer’s patients. I should note that strong cautions have already been issued with respect to the use of these medications in […]

Applying statistics in science will likely remain unreasonably difficult in my life time: but I have no intention of changing careers.

This post is by Keith. image   (Image from deviantart.com) There are a couple posts I have been struggling to put together, one is on what science is or should be (drawing on Charles Peirce). The other is on why a posterior is not a posterior is not a posterior: even if mathematically equivalent – they […]

How to do a descriptive analysis using regression modeling?

Freddy Garcia writes: I read your post Vine regression?, and your phrase “I love descriptive data analysis!” make me wonder: How to do a descriptive analysis using regression models? Maybe my question could be misleading to an statistician, but I am a economics student. So we are accustomed to think in causal terms when we […]

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

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 […]

Cloak and dagger

[cat picture] 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 […]

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

[cat picture] 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 […]

Vine regression?

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 […]

Storytelling as predictive model checking

[cat picture] 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 […]

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 […]

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 […]

Come and work with us!

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 […]

Stan is hiring! hiring! hiring! hiring!

[insert picture of adorable cat entwined with Stan logo] We’re hiring postdocs to do Bayesian inference. We’re hiring programmers for Stan. We’re hiring a project manager. How many people we hire depends on what gets funded. But we’re hiring a few people for sure. We want the best best people who love to collaborate, who […]

No evidence of incumbency disadvantage?

Several years ago I learned that the incumbency advantage in India was negative! There, the politicians are so unpopular that when they run for reelection they’re actually at a disadvantage, on average, compared to fresh candidates. At least, that’s what I heard. But Andy Hall and Anthony Fowler just wrote a paper claiming that, no, […]