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Category: Unexpectedly Difficult Statistical Concepts

[134] Figuring Out Figure 1

Posted on March 19, 2026March 19, 2026 by Joe Simmons

A few years ago our Journal Club discussed an interesting methods paper entitled, “Putting Psychology to the Test: Rethinking Model Evaluation Through Benchmarking and Prediction” (.htm). This post describes my attempt to understand what’s happening in Figure 1 of that paper, which shows that extremely simple experiments can generate extremely negative R2s. I learned a…

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[133] Heterofriendly: The Intuition for Why You Always Need Robust Standard Errors

Posted on March 2, 2026March 7, 2026 by Uri Simonsohn

When I taught my first PhD-level methods course, I invited students to submit questions about any topic in statistics or methodology. Six out of 10 students asked about the same topic: robust & clustered standard errors. It's clearly a topic they found both important and confusing. Psychologists basically never use robust standard errors. But they…

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[131] Bending Over Backwards:
The Quadratic Puts the U in AI

Posted on December 10, 2025December 10, 2025 by Uri Simonsohn

For a recent journal club in Barcelona, we read a just published article in the Journal of Experimental Psychology: General (JEP:G). The paper is on the impact of using gen-AI on creativity. The paper proposes an inverted U: people are most creative with moderate levels of AI use. The paper has three studies. Studies 1…

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[123] Dear Political Scientists: The binning estimator violates ceteris paribus

Posted on March 5, 2025October 10, 2025 by Uri Simonsohn

This post delves into a disagreement I have with three prominent political scientists, Jens Hainmueller, Jonathan Mummolo, and Yiqing Xu (HMX), on a fundamental methodological question: how to analyze interactions in observational data?  In 2019, HMX proposed the "binning estimator" for studying interactions, a technique that is now commonly used by political scientists.  I argued…

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[121] Dear Political Scientists: Don't Bin, GAM Instead

Posted on December 3, 2024March 5, 2025 by Uri Simonsohn

There is a 2019 paper, in the journal Political Analysis (htm), with over 1000 Google cites, titled "How Much Should We Trust Estimates from Multiplicative Interaction Models? Simple Tools to Improve Empirical Practice".   The paper is not just widely cited, but is also actually influential. Most political science papers estimating interactions now-a-days, seem to…

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[120] Off-Label Smirnov: How Many Subjects Show an Effect in Between-Subjects Experiments?

Posted on September 16, 2024September 16, 2024 by Uri Simonsohn

There is a classic statistical test known as the Kolmogorov-Smirnov (KS) test (Wikipedia). This post is about an off-label use of the KS-test that I don’t think people know about (not even Kolmogorov or Smirnov), and which seems useful for experimentalists in behavioral science and beyond (most useful, I think, for clinical trials and field…

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[103] Mediation Analysis is Counterintuitively Invalid

Posted on September 26, 2022September 6, 2023 by Uri Simonsohn

Mediation analysis is very common in behavioral science despite suffering from many invalidating shortcomings. While most of the shortcomings are intuitive [1], this post focuses on a counterintuitive one. It is one of those quirky statistical things that can be fun to think about, so it would merit a blog post even if it were…

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[99] Hyping Fisher: The Most Cited 2019 QJE Paper Relied on an Outdated Stata Default to Conclude Regression p-values Are Inadequate

Posted on October 13, 2021October 27, 2021 by Uri Simonsohn

The paper titled "Channeling Fisher: Randomization Tests and the Statistical Insignificance of Seemingly Significant Experimental Results" (.htm) is currently the most cited 2019 article in the Quarterly Journal of Economics (372 Google cites). It delivers bad news to economists running experiments: their p-values are wrong. To get correct p-values, the article explains, they need to…

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[91] p-hacking fast and slow: Evaluating a forthcoming AER paper deeming some econ literatures less trustworthy

Posted on September 15, 2020August 16, 2021 by Uri Simonsohn

The authors of a forthcoming AER article (.pdf), "Methods Matter: P-Hacking and Publication Bias in Causal Analysis in Economics", painstakingly harvested thousands of test results from 25 economics journals to answer an interesting question: Are studies that use some research designs more trustworthy than others? In this post I will explain why I think their…

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[88] The Hot-Hand Artifact for Dummies & Behavioral Scientists

Posted on May 27, 2020November 18, 2020 by Uri Simonsohn

A friend recently asked for my take on the Miller and Sanjurjo's (2018; pdf) debunking of the hot hand fallacy. In that paper, the authors provide a brilliant and surprising observation missed by hundreds of people who had thought about the issue before, including the classic Gilovich, Vallone, & Tverksy (1985 .htm). In this post:…

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Recent Posts

  • [134] Figuring Out Figure 1
  • [133] Heterofriendly: The Intuition for Why You Always Need Robust Standard Errors
  • [132] statuser: R in user-friendly mode
  • [131] Bending Over Backwards:
    The Quadratic Puts the U in AI
  • [130] ResearchBox: Even Easier to Use and More Transparently Permanent than Before

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Posts on similar topics

Unexpectedly Difficult Statistical Concepts
  • [134] Figuring Out Figure 1
  • [133] Heterofriendly: The Intuition for Why You Always Need Robust Standard Errors
  • [131] Bending Over Backwards:
    The Quadratic Puts the U in AI
  • [123] Dear Political Scientists: The binning estimator violates ceteris paribus
  • [121] Dear Political Scientists: Don't Bin, GAM Instead
  • [120] Off-Label Smirnov: How Many Subjects Show an Effect in Between-Subjects Experiments?
  • [103] Mediation Analysis is Counterintuitively Invalid
  • [99] Hyping Fisher: The Most Cited 2019 QJE Paper Relied on an Outdated Stata Default to Conclude Regression p-values Are Inadequate
  • [91] p-hacking fast and slow: Evaluating a forthcoming AER paper deeming some econ literatures less trustworthy
  • [88] The Hot-Hand Artifact for Dummies & Behavioral Scientists

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© 2021, Uri Simonsohn, Leif Nelson, and Joseph Simmons. For permission to reprint individual blog posts on DataColada please contact us via email..