Category: Statistics

When “nudge” doesn’t work: Medication Reminders to Outcomes After Myocardial Infarction

Gur Huberman points to this news article by Aaron Carroll, “Don’t Nudge Me: The Limits of Behavioral Economics in Medicine,” which reports on a recent study by Kevin Volpp et al. that set out “to determine whether a system of medication reminders using financial incentives and social support delays subsequent vascular events in patients following […]

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The Netflix Data War

A recent article in the Wall Street Journal, “At Netflix, Who Wins When It’s Hollywood vs. the Algorithm?” by Shalini Ramachandran and Joe Flint details some of the internal debates within Netflix between the Los Angeles-based content tea…

a glaringly long explanation

It is funny that, when I am teaching the rudiments of Bayesian statistics to my undergraduate students in Paris-Dauphine, including ABC via Rasmus’ socks, specific questions about the book (The Bayesian Choice) start popping up on X validated! Last week was about the proof that ABC is exact when the tolerance is zero. And the […]

Comparing racism from different eras: If only Tucker Carlson had been around in the 1950s he could’ve been a New York Intellectual.

TV commentator Carlson in 2018 recently raised a stir by saying that immigration makes the United States “poorer, and dirtier, and more divided,” which reminded me of this rant from literary critic Alfred Kazin in 1957: Kazin put it in his diary and Carlson broadcast it on TV, so not quite the same thing. But […]

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Comparing racism from different eras: If only Tucker Carlson had been around in the 1950s he could’ve been a New York Intellectual.

TV commentator Carlson in 2018 recently raised a stir by saying that immigration makes the United States “poorer, and dirtier, and more divided,” which reminded me of this rant from literary critic Alfred Kazin in 1957: Kazin put it in his diary and Carlson broadcast it on TV, so not quite the same thing. But […]

The post Comparing racism from different eras: If only Tucker Carlson had been around in the 1950s he could’ve been a New York Intellectual. appeared first on Statistical Modeling, Causal Inference, and Social Science.

Classifying yin and yang using MRI

Zad Chow writes: I wanted to pass along this study I found a while back that aimed to see whether there was any possible signal in an ancient Chinese theory of depression that classifies major depressive disorder into “yin” and “yang” subtypes. The authors write the following, The “Yin and Yang” theory is a fundamental […]

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Classifying yin and yang using MRI

Zad Chow writes: I wanted to pass along this study I found a while back that aimed to see whether there was any possible signal in an ancient Chinese theory of depression that classifies major depressive disorder into “yin” and “yang” subtypes. The authors write the following, The “Yin and Yang” theory is a fundamental […]

The post Classifying yin and yang using MRI appeared first on Statistical Modeling, Causal Inference, and Social Science.

vtreat Variable Importance

vtreat‘s purpose is to produce pure numeric R data.frames that are ready for supervised predictive modeling (predicting a value from other values). By ready we mean: a purely numeric data frame with no missing values and a reasonable number of columns (missing-values re-encoded with indicators, and high-degree categorical re-encode by effects codes or impact codes). … Continue reading vtreat Variable Importance

Following an idea to its logical conclusion

Following an idea to its logical conclusion might be extrapolating a model beyond its valid range. Suppose you have a football field with area A. If you make two parallel sides twice as long, then the area will be 2A. If you double the length of the sides again, the area will be 4A. Following this […]

Why do sociologists (and bloggers) focus on the negative? 5 possible explanations. (A post in the style of Fabio Rojas)

Fabio Rojas asks why the academic field of sociology seems so focused on the negative. As he puts it, why doesn’t the semester begin with the statement, “Hi, everyone, this is soc 101, the scientific study of society. In this class, I’ll tell you about how American society is moving in some great directions as […]

The post Why do sociologists (and bloggers) focus on the negative? 5 possible explanations. (A post in the style of Fabio Rojas) appeared first on Statistical Modeling, Causal Inference, and Social Science.

Why do sociologists (and bloggers) focus on the negative? 5 possible explanations. (A post in the style of Fabio Rojas)

Fabio Rojas asks why the academic field of sociology seems so focused on the negative. As he puts it, why doesn’t the semester begin with the statement, “Hi, everyone, this is soc 101, the scientific study of society. In this class, I’ll tell you about how American society is moving in some great directions as […]

The post Why do sociologists (and bloggers) focus on the negative? 5 possible explanations. (A post in the style of Fabio Rojas) appeared first on Statistical Modeling, Causal Inference, and Social Science.

Technological optimism

Kevin Kelly is one of the most optimistic people writing about technology, but there’s a nuance to his optimism that isn’t widely appreciated. Kelly sees technological progress as steady and inevitable, but not monotone. He has often said that new technologies create almost as many problems as they solve. Maybe it’s 10 steps forward and […]

Quoting Concatenate

In our last note we used wrapr::qe() to help quote expressions. In this note we will discuss quoting and code-capturing interfaces (interfaces that capture user source code) a bit more. My position on code-capturing interfaces (or non-standard-evaluation/NSE) is: if poorly handled, they can be a large interface price/risk to pay for the minor convenience of … Continue reading Quoting Concatenate

Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists”

Teppo Felin sends along this article with Mia Felin, Joachim Krueger, and Jan Koenderink on “surprise-hacking,” and writes: We essentially see surprise-hacking as the upstream, theoretical cousin of p-hacking. Though, surprise-hacking can’t be resolved with replication, more data or preregistration. We use perception and priming research to make these points (linking to Kahneman and priming, […]

The post Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists” appeared first on Statistical Modeling, Causal Inference, and Social Science.

Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists”

Teppo Felin sends along this article with Mia Felin, Joachim Krueger, and Jan Koenderink on “surprise-hacking,” and writes: We essentially see surprise-hacking as the upstream, theoretical cousin of p-hacking. Though, surprise-hacking can’t be resolved with replication, more data or preregistration. We use perception and priming research to make these points (linking to Kahneman and priming, […]

The post Surprise-hacking: “the narrative of blindness and illusion sells, and therefore continues to be the central thesis of popular books written by psychologists and cognitive scientists” appeared first on Statistical Modeling, Causal Inference, and Social Science.

How we should they carry out repeated cross-validation? They would like a third expert opinion…”

Someone writes: I’m a postdoc studying scientific reproducibility. I have a machine learning question that I desperately need your help with. . . . I’m trying to predict whether a study can be successfully replicated (DV), from the texts in the original published article. Our hypothesis is that language contains useful signals in distinguishing reproducible […]

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“My advisor and I disagree on how we should carry out repeated cross-validation. We would love to have a third expert opinion…”

Youyou Wu writes: I’m a postdoc studying scientific reproducibility. I have a machine learning question that I desperately need your help with. My advisor and I disagree on how we should carry out repeated cross-validation. We would love to have a third expert opinion… I’m trying to predict whether a study can be successfully replicated […]

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