VIF is often very subtle. The important info lies in the space of the smallest PCA dimensions.
See my {VisCollin} #rstats pkg, friendly.github.io/VisCollin/

Notation corner: When you have several different expressions that are mathematically equivalent, you don’t have to choose just one!
statmodeling.stat.columbia.edu/2026/03/25/n...

That’s a great news for the R community! Congratulations @heathrturnr.fosstodon.org.ap.brid.gy!

#rstats #dataviz #psy6136
Lecture 9 for my course in Categorical Data Analysis-- Count Data Models
📋 Materials: friendly.github.io/psy6136/#GLM...
🎞️ Slides: friendly.github.io/psy6136/lect...

Book cover for https://oliviergimenez.github.io/banana-book/

📘 New book out soon !

I’m excited to share that 𝐁𝐚𝐲𝐞𝐬𝐢𝐚𝐧 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 𝐨𝐟 𝐂𝐚𝐩𝐭𝐮𝐫𝐞-𝐑𝐞𝐜𝐚𝐩𝐭𝐮𝐫𝐞 𝐃𝐚𝐭𝐚 𝐰𝐢𝐭𝐡 𝐇𝐢𝐝𝐝𝐞𝐧 𝐌𝐚𝐫𝐤𝐨𝐯 𝐌𝐨𝐝𝐞𝐥𝐬: 𝐓𝐡𝐞𝐨𝐫𝐲 𝐚𝐧𝐝 𝐂𝐚𝐬𝐞 𝐒𝐭𝐮𝐝𝐢𝐞𝐬 𝐢𝐧 𝐑 𝐚𝐧𝐝 𝐍𝐈𝐌𝐁𝐋𝐄 is being published by Chapman & Hall / CRC Press

Hope it’s useful to students, researchers, and practitioners

#StatisticalEcology #NIMBLE

Three pictures of cats. Left: A domestic cat with leg over head, tongue out, washing itself, label is "GLM" Middle: A tiger in same pose, label is "GLMM" RIght: many cats together in same pose, label is "FIXED EFFECTS"

No matter the size or number, cats are always cats

arXiv:2404.05118v1 Announce Type: new Abstract: The BayesPPDSurv (Bayesian Power Prior Design for Survival Data) R package supports Bayesian power and type I error calculations and model fitting using the power and normalized power priors incorporating historical data with for the analysis of time-to-event outcomes. The package implements the stratified proportional hazards regression model with piecewise constant hazard within each stratum. The package allows the historical data to inform the treatment effect parameter, parameter effects for other covariates in the regression model, as well as the baseline hazard parameters. The use of multiple historical datasets is supported. A novel algorithm is developed for computationally efficient use of the normalized power prior. In addition, the package supports the use of arbitrary sampling priors for computing Bayesian power and type I error rates, and has built-in features that semi-automatically generate sampling priors from the historical data. We demonstrate the use of BayesPPDSurv in a comprehensive case study for a melanoma clinical trial design.

arXiv📈🤖
BayesPPDSurv: An R Package for Bayesian Sample Size Determination Using the Power and Normalized Power Prior for Time-To-Event Data
By

Fact checking Moravec's paradox This famous aphorism is neither true nor useful

A nice illustration of collider bias, in case anybody needs one. And it's about AI! What's not to love!?
@dingdingpeng.the100.ci
@p-hunermund.com

(in the US. Where else?)

Understanding Basis Spline (B-spline) By Working Through Cox-deBoor Algorithm | Everyday Is A School Day I finally understood B-splines by working through the Cox-deBoor algorithm step-by-step, discovering they're just weighted combinations of basis functions that make non-linear regression linear. What ...

I finally understood B-splines by working through the Cox-deBoor algorithm step-by-step, discovering they’re just weighted combo of basis functions that make non-linear regression linear. What surprised me is going through Bayesian statistics helped me understand the engine behind the model! #rstats

On the plus side, LLMs also reduce barriers for non-native speakers, facilitate the discovery of prior literature, and remove traditional signals of scientific quality such as language complexity. www.science.org/doi/10.1126/...

Hélas, I can relate. I’ve never thought that my accent is “charmant”.

A periodic reminder in #statistics:

📘 An interesting initial book release by David Rossell on variable and model selection:

👉 davidrusi.github.io/modelSelecti...

it provides accessible material for students learning the fundamentals of high-dimensional model selection, and it documents the R package modelSelection (formerly mombf).

Fred Ramsdell, who received the Nobel Prize for Physiology or Medicine yesterday for work on immunology, hasn't been informed of his win as he's "off the grid" hiking, and can't be contacted.

www.theguardian.com/science/2025...

Data visualisation using R, for researchers who don’t use R by Emily Nordmann, Phil McAleer, Wilhelmiina Toivo, Helena Paterson and Lisa DeBruine
#RStats
bigbookofr.com/chapters/data%20visualiz...

Same here. That was really easy to guess, it’s true 😅

Elucidating some common biases in randomized controlled trials using directed acyclic graphs Although the ideal randomized clinical trial is the gold standard for causal inference, real randomized trials often suffer from imperfections that may hamper causal effect estimation. Stating the estimand of interest can help reduce confusion about what is being estimated, but it is often difficult to determine what is and is not identifiable given a trial’s specific imperfections. We demonstrate how directed acyclic graphs can be used to elucidate the consequences of common imperfections, such as noncompliance, unblinding, and drop-out, for the identification of the intention-to-treat effect, the total treatment effect and the physiological treatment effect. We assert that the physiological treatment effect is not identifiable outside a trial with perfect compliance and no dropout, where blinding is perfectly maintained

Table 1 showing the Identifiability of target estimands depending on whether there is blinding, full compliance, and no drop-out

An example DAG from the paper. Fig. 4: A blinded trial with noncompliance. U are unobserved confounders, Z is treatment assignment, C is compliance, X is the realized treatment, S is the subject's physical and mental health status, Xself and Xcln are the treatment that the participant and the clinician believed the participant received, Y is the outcome.

Just finished reading this *excellent* article by Gabriel et al. which discusses which effects can be identified in randomized controlled trials. With DAGs!>

link.springer.com/article/10.1...

Positron for RStudio Users: A Gentle Introduction, Thu, Oct 9, 2025, 6:00 PM | Meetup Curious about Positron, the new open-source data science IDE from Posit? This session will walk RStudio users through the basics of Positron, highlight familiar features, a

🚀 Curious about Positron, Posit’s new open-source IDE?

This session shows RStudio users the basics, what’s new, and how it fits your workflow with @ivelasq3.bsky.social (Posit, PBC)

#RStats #DataScience #Positron #rladies

Thursday 09 October, 11am CT | 6:00 PM CAT

www.meetup.com/rladies-gabo...

Europe thinks that free and private communication is not a fundamental right.

Overview of current support and opposition for the Chat Control legislation by Patrick Breyer (https://www.patrick-breyer.de/en/posts/chat-control/). Countries opposing include the Netherlands, Belgium, Luxembourg, Austria, Czech Republic, Poland, Slovakia, Finland, and Estonia. Undecided countries are Germany, Slovenia, Romania, and Greece. All remaining member states supports Chat Control.

Germany's position has been reverted to UNDECIDED.

Despite expressing concerns about breaking end-to-end encryption, Germany refrained from taking a definitive stance on the Chat Control proposal during the September 12th LEWP meeting. A willingness to negotiate and compromise remains.

A Deep Dive Into DifferentialEquations.jl | JuliaCon Global 2025 | Rackauckas, Smith YouTube video by The Julia Programming Language

DifferentialEquations.jl is many things, and lots of people only use a small portion of it. Check out the JuliaCon 2025 workshop: introduces many aspects of the packages that the developers feel are underutilized and under-understood!

#julialang #sciml

www.youtube.com/watch?v=lSGF...

catholic church: always on the right side of the history 🙄

[pope leo XIV says that the holy see doesn’t pronounce the word g3nocid3]

The anti-autocracy handbook: how scientists can cope with democratic backsliding. This guide is a call to action, resilience, and collective defence of #democracy and #academicfreedom in the face of mounting authoritarianism zenodo.org/records/1569... @EU_Commission

A Bayesian Hierarchical Mixture Cure Modelling Framework to Utilize Multiple Survival Datasets for Long‐Term Survivorship Estimates: A Case Study From Previously Untreated Metastatic Melanoma Time to an event of interest over a lifetime is a central measure of the clinical benefit of an intervention used in a health technology assessment (HTA). Within the same trial, multiple end-points m...

Bayesian Hierarchical Mixture Cure Modelling Framework to Utilize Multiple Survival Datasets for Long-Term Survivorship Estimates #stats

Revealed: Big tech’s new datacentres will take water from the world’s driest areas Amazon, Google and Microsoft are building datacentres in water-scarce parts of five continents

Any potential gain from a switch to renewables and tech-heavy futures is inevitably undone if the underlying system of extractivist colonial enterprises and growth at all costs remains unchanged. The suffering just gets shifted to new places.
www.theguardian.com/environment/...

Bill Gates: Within 10 years, AI will replace many doctors and teachers—humans won't be needed 'for most things' A new era of "free intelligence" powered by AI will change the way humans work, says billionaire Microsoft co-founder Bill Gates.

AI’s anwers are still so biases and prompt-dependent, I don’t see how it could replace humans. www.cnbc.com/2025/03/26/b...

#r code written by AI seems to be unnecessarily complicate.

Alluvial diagram showing growth form patterns across palm subfamilies. The visualization flows from left to right, connecting palm subfamilies (Arecoideae, Calamoideae, Ceroxyloideae, and Coryphoideae) to growth forms (Erect, Non-erect, and both) to stem types (Solitary Stem, Clustered Stems, and both). The diagram reveals distinctive patterns: Arecoideae palms show diverse growth habits, Calamoideae are predominantly erect with clustered stems, Ceroxyloideae show a mix of growth forms, and Coryphoideae are mainly non-erect with solitary stems. The flow width represents the percentage of species with each characteristic.

📊 #TidyTuesday – 2025 W11 | Palm Trees
.
🔗: stevenponce.netlify.app/data_visuali...
.
#rstats | #r4ds | #dataviz | #ggplot2

Preprint sites bioRxiv and medRxiv launch new era of independence The popular repositories, where life scientists post research before peer review, will be managed by a new organization called openRxiv.

bioRxiv and medRxiv will be managed by a new organization called openRxiv. www.nature.com/articles/d41...