Two years ago, I had an idea, one that evolved over time as I kept reading and learning. Today, a major first part of that idea has just become my first PhD preprint, now publicly available on PsyArxiv. Let me tell you a bit more about the story behind it... while I prepare the submission.

I haven't read this book yet, but the authors (Grant & Di Tanna) know their stuff, and they provide code for every script/engine. Meta- and mega-analysis one of those places where Bayes is natural and often easier than non-Bayes. bayesian-ma.net

Super grateful to the WM team for such an exciting project 🥹🗺️🤍 You can check the slides of the @assc28.bsky.social presentation at| www.researchgate.net/publication/...

Six years of revisions for one of the best papers I've ever read. Seriously, a must-read: from the underlying theoretical logic of statistical modeling to the most efficient programming of models in Stan (I still remember their four-dimensional arrays for RTs!).

"Even a scientific demigod such as Gottfried Leibniz faltered when confronted with a simple problem in probability theory. Or perhaps there are no simple problems in probability theory!" (Wagenmakers & Matzke, 2024, p. 83). www.bayesianspectacles.org/free-course-...

🤓¡Primer paper de mi tesis! La historia de cómo aprendí a modelar un experimento de aprendizaje implícito. Modelar es muy poderoso: permite simular qué pasaría si asumo que tengo ruido de medida y de muestreo. ¿Tendría potencia para detectar mi efecto teórico? authors.elsevier.com/a/1km4d,H2pb...

Ideas para tatuarme en toda la piel:

I just read the paper ‘The misalignment of incentives in academic publishing and implications for journal reform’ and loved it. It gives a very illustrative overview of the roles of journals and I found it inspiring to see all the alternatives that are working! www.pnas.org/doi/10.1073/...

You write: Random intercepts were included for each subject. I read: 𝗢𝗻𝗹𝘆 random intercepts were included for each subject. #stats

Introducing PowerLMM.js! A new tool for power analysis of longitudinal linear mixed-effects models (LMMs) – with support for missing data, plus non-inferiority and equivalence tests. powerlmmjs.rpsychologist.com Would really appreciate your feedback as I refine this app! Details below 🧵👇

Our JSS article is out! And now I get to focus on {marginaleffects} 1.0.0. Stay tuned. www.jstatsoft.org/article/view...

Doing a deeper dive into reflective vs. formative modeling, thanks to some wonderful reviewers. #StatsSky #AcademicSky pdfs.semanticscholar.org/d156/8a44bb3...

Frameworks like GLLAMM (Skrondal & Rabe-Hesketh, 2004) or GLVM (Muthén, 2002) will be the future of psychometrics in the experimental world. They allow us to estimate correlations between experimental measures of latent cognitive processes with less uncertainty than any other traditional approach!