Our book also made a similar amount (divided over three authors).
10.03.2026 07:31
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Our book also made a similar amount (divided over three authors).
LOL; we ourselves (me included) just forgot to anonymize a response letter. @mattgoldrick.bsky.social
Yes, I have also done that in the past and nothing happened. Of course, technically it breaks the anonymity, but I am actually unsure about the value of anonymity. Author names is valuable prior information for a reviewer (but it might penalize new people, I have to admit).
Authors sometimes forget to anonymize the code :). So double-blind doesn't really work.
I would ask the editor or look at their web page to see what their policy is. That said, usually even with double blind articles that I review, I can quite often easily guess who the authors are.
Apparently @planetmoney.bsky.social does not know the difference between reproducing an analysis using the provided code and data, and replicating an experiment's results with a new experiment:
www.npr.org/2026/02/27/n...
New open-access paper with @shravanvasishth.bsky.social: "Context ameliorates but does not eliminate garden-pathing: Novel insights from latent-process modeling" doi.org/10.1016/j.jm...
New preprint led by Pia Schoknecht:
Local coherence effects are task sensitive: Evidence from event-related potentials in German
doi.org/10.31234/osf...
It is pure torture. That's probably why I felt compelled to become a linguist.
At best it has two interpretations, which is what is bugging me. The interpretation that jumps out at me and bugs me:
Talks can not be short -> It is possible to set up a talk such that it is not short.
Of course, the rest of the post makes it clear what the interpretation is, but still...
The distinction between "cannot" and "can not" completely changes the meaning of the sentence :)
It always bugs me when people write can not when they really mean cannot. I want to shout: WHAT IS WRONG WITH YOU? :)
The content is less than 200 pages. My book, published by the same publisher in 2021, which is a bit longer, costs 28 Euros for the digital edition. Why the big discrepancy in price?
122 Euros for the digital edition? Really?
New preprint with @tallinzen.bsky.social and @shravanvasishth.bsky.social: We jointly model reading data from four tasks (SPR, BSPR, eye tracking, Maze) with a latent-process mixture, and find that it outperforms LLM surprisal in terms of predictive fit: arxiv.org/abs/2602.04489
Applications for the summer school on statistical methods for linguistics and psychology (Potsdam, Germany) are now open:
vasishth.github.io/smlp2026/
Oral interactive discussion with instructor without any notes or electronic aids. Time-consuming but effective.
Short-term fellowships for 2026 at the University of Potsdam, Germany (linguistics and psychology): linguistlist.org/issues/36/38...
Here is your chance to weigh in on what the psycholinguistic and machine learning community needs regarding preprocessing pipelines, software tools, and data sharing standards for eye-tracking research: An anonymous survey that lasts just 10-15 minutes: www.soscisurvey.de/OpenEye/
Keynote speakers in 2026: Dale Barr and Lisa DeBruine.
Applications for the summer school on statistical methods for linguistics and psychology (Potsdam, Germany) are now open:
vasishth.github.io/smlp2026/
a rare sighting of all three authors of The Book, all in one place:
New preprint investigating whether lossy-context surprisal can account for the locality and expectation effects found in Russian, Hindi, and Persian reading data: osf.io/preprints/ps...
We are done with the ninth Statistical Methods for Linguistics and Psychology (SMLP) summer school, Potsdam, Germany. The tenth edition is planned for 24-28 August 2026.
A common disease in academia is that for any position X there is an academic with an opposing position not-X. It's just how academics are. One can't just blindly follow one or another person's recommendation, but develop a good understanding of it oneself, and draw one's own conclusions.
I guess then we should also recommend against using p-values because they are sensitive to the likelihood function assumed? :) Who was it that gave this recommendation? I'm guessing SIngmann but maybe I'm wrong.
Because this is a frequently asked question in summer schools I teach, I am thinking about adding a video lecture on this in my online materials for the book. Do also read the online chapter from our book on this topic:
bruno.nicenboim.me/bayescogsci/...
Also:
Cumming, G. (2014). The new statistics: Why and how. Psychological science, 25(1), 7-29.
Kruschke, J. K. (2011). Bayesian assessment of null values via parameter estimation and model comparison. Perspectives on Psychological Science, 6(3), 299-312.
epub.ub.uni-muenchen.de/74222/
Some other books to read:
Royall, R. (2017). Statistical evidence: a likelihood paradigm. Routledge.
Spiegelhalter, D. (2024). The art of uncertainty: how to navigate chance, ignorance, risk and luck. Random House.
Spiegelhalter, D. J., Abrams, K. R., & Myles, J. P. (2004). Bayesian approaches to clinical trials and health-care evaluation. John Wiley & Sons.
You can use the credible interval to think about whether the pattern is consistent with the predicted effect. Even better if you can compare that interval to a model's a priori predicted interval. Read Spiegelhalter's 2004 book: