Oops! This time with the link to the PsyArXiv preprint:
doi.org/10.31234/osf...
Excited that our paper on the Gambler's Fallacy for Probability Judgments is now "in press" at Judgment and Decision Making!
@sjdm-tweets.bsky.social @eadmnews.bsky.social
Fortunately for us, Judgment and Decision Making agreed to review what Psychological Science would not.
Backstory: In January, Psychological Science desk-rejected our initial critique of the gambler's fallacy article they published in 2025 because they were already considering a different critique of the same article (that was a new one for me). We still don't know the status of the other critique.
Among our findings: Reasonable models of the fallacy predict both probability judgments and binary responses reasonably well, with the same parameter values. The article we critique suggested discarding all models of the fallacy that are based on probabilistic reasoning (i.e., all of them).
Excited that our paper on the Gambler's Fallacy for Probability Judgments is now "in press" at Judgment and Decision Making!
@sjdm-tweets.bsky.social @eadmnews.bsky.social
And here's an uncropped version of the figure.
If the appeal doesn’t work, try publishing elsewhere. If your criticism is strong, it will find a home. The original journal will look as if they are more interested in their reputation than in getting the science right. I’m doing a similar thing now, though not regarding a meta-analysis.
A graph showing that mean probability judgments that a streak of similar outcomes would continue were below the base rate for most terminal streak lengths greater than one, consistent with the gambler's fallacy
Revised preprint!
Science may be self-correcting, but only if the corrections are published.
A 2025 Psych Science article reported no gambler's fallacy for probability judgments w/ truly random sequences, but Yeonho Choi and I found strong evidence for the fallacy in the authors’ data.
Honored to have my in-press paper featured by SJDM!
Thanks for the plug! I just submitted the (first round of) page proofs.
New preprint!
A recent Psych Science article reported no gambler's fallacy for probability judgments w/ truly random sequences and a disconnect between such judgments and binary predictions.
Yeonho Choi and I reanalyzed the data and found very strong evidence for an effect and a much smaller gap.
I will need to change one of my examples for the German cities task.
It is interesting that two of the data points in the small data set were from that part of Texas.
A graph of predicted loss of life as a function of warning time from flash flood when there are 1,000 people at risk. With no warning, over 130 fatalities are expected. With one hour, only about 10 are expected. Those numbers are for "high force" floods with swiftly moving water. Note: the data are more than 30 years old.
It's a shame the county decided not to install a warning system (e.g., sirens) along the Guadalupe River. Here's a 30-yr-old graph showing the benefit of warning time for forceful floods w/ pop. at risk = 1000. Would love an update based on more data.
Paper: onlinelibrary.wiley.com/doi/abs/10.1...
Nice paper w/ some great points. Maybe see Michel Regenwetter's papers on generalizing to "people." Other examples: Hershey & Shoemaker (1980, reflection effect) and - self-serving - one of mine (2016, do multiple plays eliminate certainty/possibility effects?). Still a role for btw-Ss exps, imho.
A table listing some limitations of meta-analyses and how metastidies address them. Metastudies provide advantages related to applicability; time, effort, and money; publication bias; statistical precision and power; generalizability; and the interpretation of results for moderators.
Wonderful paper! For more on purposive variation, see this 2022 paper on metastudies: journals.sagepub.com/doi/10.1177/...
Free postprint: osf.io/preprints/ps...
It's like Simonsohn et al.'s new mix-and-match method, but with more attention to moderation, generalizability, and statistical power.
When completely described, the certain option includes a negation, as in "200 people will be saved and 400 people will not be saved."
Some theories have no place for such negations and so don't make clear predictions. Others predict no framing effect in choices between completely described options.
New PsyArXiv preprint! osf.io/preprints/ps...
Risky-choice framing effects persist when option descriptions are matched in gains and losses and even when the options are completely described.
(Last year's Psych Science results replicated nicely in a larger census-matched sample!)
Teaching tidbit for JDM/risk perception: NPR story on a fire in a battery storage facility is a perfect example of Slovic's "signal potential." Link in comment.
“Ultimately, the incident has tremendous potential to derail the industry, not just within California, but across all of North America.”
I was there! It was raining the whole time, and people were undeterred.
An appeal to anyone conducting a "megastudy": Treat it like a big counterbalanced experiment (as in a "metastudy"; see link to a not-so-new paper), so you don't end up with some of the same problems as meta-analyses, such as having the features of the interventions being correlated and imbalanced.
An appeal to anyone overseeing a "megastudy": Treat the whole thing like a big counterbalanced experiment (as in a "metastudy"; see the link), so you don't end up with some of the same problems as meta-analyses, such as having the features of the interventions being correlated and imbalanced.
I'm surprised the X logo has not spouted little clockwise feet to resemble a swastika. Graphic designers, where are you?
Wonderful paper! At the risk of appearing/being self-serving, here are three papers on perceptions of energy and water use (not perceptions of others' beliefs) that used similar methods (mixed models):
www.pnas.org/doi/full/10....
www.sciencedirect.com/science/arti...
www.pnas.org/doi/full/10....
Our daughter McKenzie (not pictured) is one of the fired Presidential Management Fellows featured in this story. Feel free to share.
DOGE has never been and never will be about efficiency. There is zero chance that firing these talented, dedicated young employees improves government efficiency.
