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Archive of posts filed under the Causal Inference category.

What to do when your measured outcome doesn’t quite line up with what you’re interested in?

Matthew Poes writes: I’m writing a research memo discussing the importance of precisely aligning the outcome measures to the intervention activities. I’m making the point that an evaluation of the outcomes for a given intervention may net null results for many reasons, one of which could simply be that you are looking in the wrong […]

Don’t get fooled by observational correlations

Gabriel Power writes: Here’s something a little different: clever classrooms, according to which physical characteristics of classrooms cause greater learning. And the effects are large! Moving from the worst to the best design implies a gain of 67% of one year’s worth of learning! Aside from the dubiously large effect size, it looks like the […]

Discussion of effects of growth mindset: Let’s not demand unrealistic effect sizes.

Shreeharsh Kelkar writes: As a regular reader of your blog, I wanted to ask you if you had taken a look at the recent debate about growth mindset [see earlier discussions here and here] that happened on theconversation.com. Here’s the first salvo by Brooke McNamara, and then the response by Carol Dweck herself. The debate […]

The gaps between 1, 2, and 3 are just too large.

Someone who wishes to remain anonymous points to a new study of David Yeager et al. on educational mindset interventions (link from Alex Tabarrok) and asks: On the blog we talk a lot about bad practice and what not to do. Might this be an example of how *to do* things? Or did they just […]

John Hattie’s “Visible Learning”: How much should we trust this influential review of education research?

Dan Kumprey, a math teacher at Lake Oswego High School, Oregon, writes: Have you considered taking a look at the book Visible Learning by John Hattie? It seems to be permeating and informing reform in our K-12 schools nationwide. Districts are spending a lot of money sending their staffs to conferences by Solution Tree to […]

When anyone claims 80% power, I’m skeptical.

A policy analyst writes: I saw you speak at ** on Bayesian methods. . . . I had been asked to consult on a large national evaluation of . . . [details removed to preserve anonymity] . . . and had suggested treading carefully around the use of Bayesian statistics in this study (basing it […]

Let’s be open about the evidence for the benefits of open science

A reader who wishes to remain anonymous writes: I would be curious to hear your thoughts on is motivated reasoning among open science advocates. In particular, I’ve noticed that papers arguing for open practices have seriously bad/nonexistent causal identification strategies. Examples: Kidwell et al. 2017, Badges to Acknowledge Open Practices: A Simple, Low-Cost, Effective Method […]

China air pollution regression discontinuity update

Avery writes: There is a follow up paper for the paper “Evidence on the impact of sustained exposure to air pollution on life expectancy from China’s Huai River policy” [by Yuyu Chen, Avraham Ebenstein, Michael Greenstone, and Hongbin Li] which you have posted on a couple times and used in lectures. It seems that there […]

Data-based ways of getting a job

Bart Turczynski writes: I read the following blog with a lot of excitement: Then I reread it and paid attention to the graphs and models (which don’t seem to be actual models, but rather, well, lines.) The story makes sense, but the science part is questionable (or at least unclear.) Perhaps you’d like to have […]

He wants to know what to read and what software to learn, to increase his ability to think about quantitative methods in social science

A law student writes: I aspire to become a quantitatively equipped/focused legal academic. Despite majoring in economics at college, I feel insufficiently confident in my statistical literacy. Given your publicly available work on learning basic statistical programming, I thought I would reach out to you and ask for advice on understanding modeling and causal inference […]

About that claim in the NYT that the immigration issue helped Hillary Clinton? The numbers don’t seem to add up.

Today I noticed an op-ed by two political scientists, Howard Lavine and Wendy Rahm, entitled, “What if Trump’s Nativism Actually Hurts Him?”: Contrary to received wisdom, however, the immigration issue did not play to Mr. Trump’s advantage nearly as much as commonly believed. According to our analysis of national survey data from the American National […]

Trying to make some sense of it all, but I can see it makes no sense at all . . . stuck in the middle with you

“Mediation analysis” is this thing where you have a treatment and an outcome and you’re trying to model how the treatment works: how much does it directly affect the outcome, and how much is the effect “mediated” through intermediate variables. Fabrizia Mealli was discussing this with me the other day, and she pointed out that […]

About that quasi-retracted study on the Mediterranean diet . . .

Some people asked me what I thought about this story. A reporter wrote to me about it last week, asking if it looked like fraud. Here’s my reply: Based on the description, there does not seem to be the implication of fraud. The editor’s report mentioned “protocol deviations, including the enrollment of participants who were […]

Some experiments are just too noisy to tell us much of anything at all: Political science edition

Sointu Leikas pointed us to this published research article, “Exposure to inequality affects support for redistribution.” Leikas writes that “it seems to be a really apt example of “researcher degrees of freedom.’” Here’s the abstract of the paper: As the world’s population grows more urban, encounters between members of different socioeconomic groups occur with greater […]

How to reduce Type M errors in exploratory research?

Miao Yu writes: Recently, I found this piece [a news article by Janet Pelley, Sulfur dioxide pollution tied to degraded sperm quality, published in Chemical & Engineering News] and the original paper [Inverse Association between Ambient Sulfur Dioxide Exposure and Semen Quality in Wuhan, China, by Yuewei Liu, published in Environmental Science & Technology]. Air […]

Does “status threat” explain the 2016 presidential vote?

Steve Morgan writes: The April 2018 article of Diana Mutz, Status Threat, Not Economic Hardship, Explains the 2016 Presidential Vote, was published in the Proceedings of the National Academy of Sciences and contradicts prior sociological research on the 2016 election. Mutz’s article received widespread media coverage because of the strength of its primary conclusion, declaimed […]

“16 and Pregnant”

Ted Joyce writes: In December 2015 the AER published an article, “Media Influences on Social Outcomes: The Impact of MTV’s 16 and Pregnant on Teen Childbearing,” by Melissa Kearney and Phil Levine [KL]. The NBER working paper of this article appeared in January of 2014. It received huge media attention as the authors claimed the […]

Early p-hacking investments substantially boost adult publication record

In a post with the title “Overstated findings, published in Science, on long-term health effects of a well-known early childhood program,” Perry Wilson writes: In this paper [“Early Childhood Investments Substantially Boost Adult Health,” by Frances Campbell, Gabriella Conti, James Heckman, Seong Hyeok Moon, Rodrigo Pinto, Elizabeth Pungello, and Yi Pan], published in Science in […]

“The Internal and External Validity of the Regression Discontinuity Design: A Meta-Analysis of 15 Within-Study-Comparisons”

Jag Bhalla points to this post by Alex Tabarrok pointing to this paper, “The Internal and External Validity of the Regression Discontinuity Design: A Meta-Analysis of 15 Within-Study-Comparisons,” by Duncan Chaplin, Thomas Cook, Jelena Zurovac, Jared Coopersmith, Mariel Finucane, Lauren Vollmer, and Rebecca Morris, which reports that regression discontinuity (RD) estimation performed well in these […]

Does adding women to corporate boards increase stock price?

Anton Kasster writes: