Just added to PowerLMM.js v0.3: Interactive power contour plots! Visualize how statistical power changes across parameter combinations. powerlmmjs.rpsychologist.com?view=contour

Just added to PowerLMM.js v0.3: Interactive power contour plots! Visualize how statistical power changes across parameter combinations. powerlmmjs.rpsychologist.com?view=contour

Wasn't that happy with how performance crashed as time points grew, so I dusted off some linear algebra to optimize the calculations. Benchmark showed a ~1Mx speedup using new implementation (with 100 time points) 😅

🎉 @rpsychologist.com 's PowerLMM.js is the online statistics application of the year 2025 🎉 powerlmmjs.rpsychologist.com - Calculate power (etc) for multilevel models - Examine effects of dropout and other important parameters - Fast! (Instant results)

Who’s gonna pay @rpsychologist.com to make a mega tool converting all g*power analysis types to an interpretable web tool like this?

New release of PowerLMM.js! Browser-based power analysis for longitudinal models with dropout. Now includes: - Power analysis summary report - Reproducible & shareable configs (URL/JSON) - Calculations validated against R - Hypothesis region visualization powerlmmjs.rpsychologist.com

Turns out proportions aren't collapsible after all. Take that, OR haters. "Globally, approximately 3.3% of the population reports using AAS, with prevalence rates of 6.4% among men [2] and 4% among women [3]."

I watched this so you don’t have to. A couple of highlights: ”I sometimes say that 'screen use', when putting that into statistical models, it’s sort of like looking at 'car use' when trying to find out why injuries are happening from car accidents” 🇳🇴 www.youtube.com/live/XKo6oUY...

Great talk by @jeremylabrecque.bsky.social "Before and after causal inference: recognizing causal questions and answering them when assumptions are violated" www.youtube.com/watch?v=9B-X...

Not sure where to start with this one. Internet gaming addiction… is a risk factor for internet gaming disorder

Regarding the expert consensus on smartphone use: let’s not forget that the related “behavioral addiction” gaming disorder, is essentially a copy-paste job. Below is a visual comparison of the ICD-11 criteria for gaming and gambling disorder—essentially a substitution of terms.

A common sentiment is “I can’t share my code because it’s messy and there might be errors” But if it’s that untrustworthy, why are you publishing the results it generates?

I see this a lot in longitudinal analysis—people assume missingness can depend on random effects (like slopes). But those aren’t conditioned on, so that kind of missingness would be non-ignorable (MNAR).

This new package for mediation is great! The user interface is *so intuitive* but the unsung hero of this software is the documentation:

Despite the well-polished workflow of this package, I tried to analyze the “useless data set” that comes with it using {mediation}. Treatment and mediator were (strongly) confounded, so we need to pay close attention to the sensitivity analysis!

To think that some scientists working in medicine will even brag about not understanding the methods used in the papers they "lead". Like it's beneath them. What a world.

This is great. It even handles binary and count outcomes appropriately!

🚨New R package! {easymediation}🚨 The *Simplest* and *Most Correct* Way to Do Causal Mediation Analysis Are you tired of explaining mediation analysis to your colleagues? Just send them this package. github.com/rpsychologis...

Step 1: Say data are MNAR Step 2: Toss in random values Step 3: Call it conservative I’ll definitely adopt this model-free way of handling MNAR, what could go wrong?

Amazing observation in a paper: people use smartphones while waiting. I’ve also observed that people read magazines they’d never touch anywhere else while waiting. Proposing a new disorder: "Compulsive Magazine Reading". Urgent need for intervention programs

Been reading up on causal prediction – let me know if I’ve got this right: Clinical prediction: Hard. Causal inference: Hard. Causal prediction: Combines the hardest parts of both. Predict outcomes we can’t observe, and evaluate models by making even more assumptions about an unobservable target.

NEW PAPER: Updated CONSORT-2025 for reporting randomised trials is now available in the @bmj.com @jama.com , @thelancet.bsky.social, @plos.org and @naturemedicine.bsky.social —> www.bmj.com/content/389/... #openscience #transparency #medsky #statssky #episky

Hear me out, psychologists are the OG vibe coders. Picking factors by squinting at scree plots, naming latent variables on instinct, fitting SEMs based on celestial drawings, and publishing without a care.

New blog post! Sometimes, when reviewing a manuscript, it's really unclear to me what precisely the authors are trying to do -- which makes it hard to evaluate the work properly. So, here's some advice for how to ensure that readers don't get lost. www.the100.ci/2025/02/17/r...

Trying to compile a list of people with active pedagogic interests in teaching statistics go.bsky.app/Qg6YSq6

Please stop telling me about risk factors. 🙏😖 (ICYMI) statsepi.substack.com/p/sorry-what...

Added a variogram to the app! I'm experimenting with showing the non-stationarity of correlations in a random slopes model.

This looks *extremely* neat. Kristoffer consistently provides exceptionally useful tools and visualizations 🤩

💙 this web app for examining multilevel models' precision & sample size planning. (Now I just need to pair it with Claude to input the numeric predictions from my verbal descriptions 😉.)

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 🧵👇

Mental Health Disorder Trends in Denmark According to Age, Calendar Period, and Birth Cohort "This cohort study found that more recent birth cohorts and calendar periods had higher sex-specific incidence rates of any mental disorder" jamanetwork.com/journals/jam...

We’re no experts but this sounds like it might be suboptimal for disseminating research.

The plot thickens

Best social media innovation of 2024: a platform that is exactly like another was 5 years ago

Whenever I accidentally see my GS recommendations it gives a harsh reminder of the state of art. Despite the field lacking understanding of GD let alone its measurement, multiple studies driven by these measures come out *every day*. At least publishing business is doing good

This is the only starter pack I want to be added to

Important question: Why is it called a *Bayesian* Bicep Curl? 🤔 And what's a Frequentist Curl?

When a study talks about various things that could bias estimates but never explicitly addresses the analysis goal in the first place

Me and @larsklintwall.bsky.social have been working on an app that will allow participants to interactively build networks of perceived causal relations. I’ve put together a demo website, that I’m soft-launching while we continue to pilot the app pecan-tool.rpsychologist.com 🧵👇

Simulation studies are essential for methods research. How well are they conducted & reported? How can we improve their quality? Out now in Psychological Methods, see 🧵 below. With @fbartos.bsky.social, @timpmorris.bsky.social, @boulesteixlaure.bsky.social, @danielheck.bsky.social & Samuel Pawel

Working on some network stuff. It's oddly satisfying going from this network spaghetti to something a bit more organized

When I started to supervise master theses, students had somehow heard of the PROCESS macro. Even some colleagues were working with it. When I looked into it, I couldn't believe what I saw. Then @dingdingpeng.the100.ci approached me to write a paper about its shortcomings. Now it reached 200 cites! 📈

This is way too accurate 😂

Oh are we doing "random confounding" again

Quote a favorite film. Gif only

ok I will build it

This is getting out of hand, we need a starter pack of starter packs

So are we doing Bayes vs NHST next?

Not very surprising. One of the most prominent and widely accepted conclusions in clinical psychology - the Dodo bird verdict - is essentially built on this (mis)interpretation. 👇

I don't think the ”problem” is tidyverse vs base R. The #rstats community's culture is shaped by non-programmers, and that's a _huge_ strength, fostering a DIY community where lots of people feel comfortable trying things out, creating resources, and getting stuff done.