Damn. This story makes me so frustrated I can’t even laugh. I can only cry. Here’s the background. A few months ago, Aleksi Reito (who sent me the adorable picture above) pointed me to a short article by Yanik Bababekov, Sahael Stapleton, Jessica Mueller, Zhi Fong, and David Chang in Annals of Surgery, “A Proposal […]

# Category: Miscellaneous Statistics

## Published in 2018

R-squared for Bayesian regression models. {\em American Statistician}. (Andrew Gelman, Ben Goodrich, Jonah Gabry, and Aki Vehtari) Voter registration databases and MRP: Toward the use of large scale databases in public opinion research. {\em Political Analysis}. (Yair Ghitza and Andrew Gelman) Limitations of “Limitations of Bayesian leave-one-out cross-validation for model selection.” {\em Computational Brain and […]

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## Published in 2018

R-squared for Bayesian regression models. {\em American Statistician}. (Andrew Gelman, Ben Goodrich, Jonah Gabry, and Aki Vehtari) Voter registration databases and MRP: Toward the use of large scale databases in public opinion research. {\em Political Analysis}. (Yair Ghitza and Andrew Gelman) Limitations of “Limitations of Bayesian leave-one-out cross-validation for model selection.” {\em Computational Brain and […]

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## Combining apparently contradictory evidence

I want to write a more formal article about this, but in the meantime here’s a placeholder. The topic is the combination of apparently contradictory evidence. Let’s start with a simple example: you have some ratings on a 1-10 scale. These could be, for example, research proposals being rated by a funding committee, or, umm, […]

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## Combining apparently contradictory evidence

I want to write a more formal article about this, but in the meantime here’s a placeholder. The topic is the combination of apparently contradictory evidence. Let’s start with a simple example: you have some ratings on a 1-10 scale. These could be, for example, research proposals being rated by a funding committee, or, umm, […]

The post Combining apparently contradictory evidence appeared first on Statistical Modeling, Causal Inference, and Social Science.

## Combining apparently contradictory evidence

I want to write a more formal article about this, but in the meantime here’s a placeholder. The topic is the combination of apparently contradictory evidence. Let’s start with a simple example: you have some ratings on a 1-10 scale. These could be, for example, research proposals being rated by a funding committee, or, umm, […]

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## “Check yourself before you wreck yourself: Assessing discrete choice models through predictive simulations”

Timothy Brathwaite sends along this wonderfully-titled article (also here, and here’s the replication code), which begins: Typically, discrete choice modelers develop ever-more advanced models and estimation methods. Compared to the impressive progress in model development and estimation, model-checking techniques have lagged behind. Often, choice modelers use only crude methods to assess how well an estimated […]

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## “Check yourself before you wreck yourself: Assessing discrete choice models through predictive simulations”

Timothy Brathwaite sends along this wonderfully-titled article (also here, and here’s the replication code), which begins: Typically, discrete choice modelers develop ever-more advanced models and estimation methods. Compared to the impressive progress in model development and estimation, model-checking techniques have lagged behind. Often, choice modelers use only crude methods to assess how well an estimated […]

The post “Check yourself before you wreck yourself: Assessing discrete choice models through predictive simulations” appeared first on Statistical Modeling, Causal Inference, and Social Science.

## What is probability?

This came up in a discussion a few years ago, where people were arguing about the meaning of probability: is it long-run frequency, is it subjective belief, is it betting odds, etc? I wrote: Probability is a mathematical concept. I think Martha Smith’s analogy to points, lines, and arithmetic is a good one. Probabilities are […]

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## What is probability?

This came up in a discussion a few years ago, where people were arguing about the meaning of probability: is it long-run frequency, is it subjective belief, is it betting odds, etc? I wrote: Probability is a mathematical concept. I think Martha Smith’s analogy to points, lines, and arithmetic is a good one. Probabilities are […]

The post What is probability? appeared first on Statistical Modeling, Causal Inference, and Social Science.

## June is applied regression exam month!

So. I just graded the final exams for our applied regression class. Lots of students made mistakes which gave me the feeling that I didn’t teach the material so well. So I thought it could help lots of people out there if I were to share the questions, solutions, and common errors. It was an […]

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## June is applied regression exam month!

So. I just graded the final exams for our applied regression class. Lots of students made mistakes which gave me the feeling that I didn’t teach the material so well. So I thought it could help lots of people out there if I were to share the questions, solutions, and common errors. It was an […]

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## Carol Nickerson explains what those mysterious diagrams were saying

A few years ago, James Coyne asked, “Can you make sense of this diagram?” and I responded, No, I can’t. At the time, Carol Nickerson wrote up explanations for two of the figures in the article in question. So if anyone’s interested, here they are: Carol Nickerson’s explanation of Figure 2 in Kok et al. […]

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## Carol Nickerson explains what those mysterious diagrams were saying

A few years ago, James Coyne asked, “Can you make sense of this diagram?” and I responded, No, I can’t. At the time, Carol Nickerson wrote up explanations for two of the figures in the article in question. So if anyone’s interested, here they are: Carol Nickerson’s explanation of Figure 2 in Kok et al. […]

The post Carol Nickerson explains what those mysterious diagrams were saying appeared first on Statistical Modeling, Causal Inference, and Social Science.

## The causal hype ratchet

Noah Haber informs us of a research article, “Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review,” that he wrote with Emily Smith, Ellen Moscoe, Kathryn Andrews, Robin Audy, Winnie Bell, Alana Brennan, Alexander Breskin, Jeremy Kane, Mahesh Karra, Elizabeth McClure, and Elizabeth Suarez, and […]

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## The causal hype ratchet

Noah Haber informs us of a research article, “Causal language and strength of inference in academic and media articles shared in social media (CLAIMS): A systematic review,” that he wrote with Emily Smith, Ellen Moscoe, Kathryn Andrews, Robin Audy, Winnie Bell, Alana Brennan, Alexander Breskin, Jeremy Kane, Mahesh Karra, Elizabeth McClure, and Elizabeth Suarez, and […]

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## Exploring model fit by looking at a histogram of a posterior simulation draw of a set of parameters in a hierarchical model

Opher Donchin writes in with a question: We’ve been finding it useful in the lab recently to look at the histogram of samples from the parameter combined across all subjects. We think, but we’re not sure, that this reflects the distribution of that parameter when marginalized across subjects and can be a useful visualization. It […]

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## Exploring model fit by looking at a histogram of a posterior simulation draw of a set of parameters in a hierarchical model

Opher Donchin writes in with a question: We’ve been finding it useful in the lab recently to look at the histogram of samples from the parameter combined across all subjects. We think, but we’re not sure, that this reflects the distribution of that parameter when marginalized across subjects and can be a useful visualization. It […]

The post Exploring model fit by looking at a histogram of a posterior simulation draw of a set of parameters in a hierarchical model 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 […]

The post Classifying yin and yang using MRI 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 […]

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