The TARGET reporting guidelines for target trial emulation studies have arrived! #EpiSky #CausalSky jamanetwork.com/journals/jam...

It's very human to only double check that a process is working when you get a weird result. It's also very bad practice, because sometimes your "right" result is due to a bad process and you will be misled. Social scientists (economists) do this kind of asymmetric checking. arxiv.org/pdf/2508.20069

Ever stared at a table of regression coefficients & wondered what you're doing with your life? Very excited to share this gentle introduction to another way of making sense of statistical models (w @vincentab.bsky.social) Preprint: doi.org/10.31234/osf... Website: j-rohrer.github.io/marginal-psy...

I'm reviewing a lot of weak target trial emulation studies these days. Like a wolf in sheep's clothes, these adopt the language & structure of target trial emulation, but don't apply the necessary care or thought. Is this the 'doom cycle'? Where every promising new tool gets dragged into the mud.

Technical writing is hard bcs "writing is thinking" but we often should tell our story not in the order we worked. Solution? I wrote a quick post on how @quarto.org 's embed shortcodes can reframe technical writing as reproducible evidence curation www.emilyriederer.com/post/quarto-... 🧵 (1/n)

It's exceedingly hard to argue that the administration & MAHA are committed to improving nutrition when they're simultaneously cutting everything from SNAP-Ed to innovative community nutrition work - cements the perception that food dyes are public health theatre. www.healthbeat.org/newyork/2025...

Serious concerns about a new cortical biomarker for pain sensitivity jamanetwork.com/journals/jam... We (with @tspisak.bsky.social, @christianbuchel.bsky.social) published a commentary on Chowdhury, Bi et al. (2025, JAMA Neurology) raising serious concerns about their reported results. 👇 1/13

This article provides an overview of the current state of handling continuous variables in healthcare research. It discusses the potential limitations of assuming a linear relationship between independent and dependent variables www.bmj.com/content/390/...

Statistics/Causal Inference folks, what are your favorite papers on why VIF is bad?

At this point, I might as well -- Here's an infographic showing different ways to include age as a predictor. The top shows two extremes, just as a plain old numerical predictor (imposes linear trajectory) vs. categorical predictor (imposes nothing whatsoever). And then three solutions in between!

Fantastic article about modeling of continuous variables! ⬇️ Shameless plug: I wrote a blog about restricted cubic spline applied to nutrition and health data: didierbrassard.github.io/posts/2023/0...

There are going to be an awful lot of analyses that need redone when people finally accept that collider bias is a major issue in unweighted analyses of UKBB data

How can we reform science? I have some ideas. But I am not sure you’ll like them, because they don’t promise much. elevanth.org/blog/2025/07...

📄 New preprint! 
The main project of my postdoctoral work is now available (not peer-reviewed yet): Estimating the effect of adhering to #CanadaFoodGuide 2019 recommendations in older adults: a target trial emulation
 🔗 www.medrxiv.org/content/10.1...

I agree, the challenges to self-correcting science are real. Tried to publish a “letter to the editor” which was rejected in the end. The editor mentioned the topic of the letter wouldn’t be of interest to readers! Wouldn’t readers also be interested to learn about flaws of a published study?

Experimentology is out today!!! A group of us wrote a free online textbook for experimental methods, available at experimentology.io - the idea was to integrate open science into all aspects of the experimental workflow from planning to design, analysis, and writing.

What is ‘Open Science’? Or, how is Open Science operationalised in survey research? Come talk to me at the #metascience2025 poster session!

Update #2, RETRACTED: 15 months after we (w @ollefolke.bsky.social and @johannarickne.bsky.social ) submitted the initial comment to the Journal, we've noticed the paper was ultimately retracted. Retraction note here: link.springer.com/article/10.1...

Friendly #rstats package development reminder to my future self: `@inheritParams` is a nice {roxygen2} feature to help you stay DRY when writing function documentation. More here: r-pkgs.org/man.html#inh... 📦 : roxygen2.r-lib.org/index.html

basically every research paper I’ve written, minus step 6.

TIL that impact factors are even weirder than I thought! Negotiated with Clarivate?! What? I didn’t think the scientific publishing system could get any stranger!

Me: "What did you learn at journal club today?" Intern: "That one day I'm going to publish a paper, and a bunch of people are going to sit around a table and rip it apart."

Academia will form these little pockets -- people whose theorizing is outrageous & supported by methods outdated since the 90s -- but once it reaches a critical size those people just review each others papers & grants, form societies, hand out awards etc, like a self-contained parallel society.

Great tips to improve your R coding experience

AI is a problem for research as well as student evaluation: "we highlight a set of best practices to mitigate the risks of paper mills using AI-assisted workflows to introduce low-quality manuscripts to the scientific literature"

Shouldn't need saying, but clearly it does "Reporting guideline checklists are not quality evaluation forms: they are guidance for writing" --> onlinelibrary.wiley.com/doi/10.1002/... ...quality/risk of bias assessment is aided by transparent reporting though.

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

When planning for data collection, especially in longitudinal studies, first consider how that data will be used. Ask yourself: - How will we combine data for analysis? - What unique IDs will allow us to do this? - How will we name/code items to combine data? - Will our data need restructuring?

"Publications typically describe the discovery as it ideally should have happened, reporting only the evidence relevant to the proposed claims."

Inspired by a recent conversation, and by this article (onlinelibrary.wiley.com/doi/10.1002/...), I have been working on a one-pager to help researchers through the process of updating published datasets if errors are ever found. I'd love any feedback!

How to deal with (multi)colinearity in a regression model? If the goal is purely to predict: even high colinearity may not matter much pubmed.ncbi.nlm.nih.gov/35016734/ and quick-fix solutions like PCA may do more harm than good onlinelibrary.wiley.com/doi/10.1002/...

Great research career advice 👇🏻

Did you know that all the fine artisanal memes from my stats lectures are available in the course repo? Reuse and remixing freely encouraged github.com/rmcelreath/s...

Avoid the shock of bad data. Tips to collect better data: cghlewis.com/blog/survey_...

New blog post! In which I explain the issue with mediation analysis and sketch out one way to deal with the underlying causal inference problem -- in just a bit over 1,000 words! If you have never found the time to read up on this, now is your chance. www.the100.ci/2025/03/20/r...

Waterfall plots present changes or differences for individual cases. While "show the data" is 👍, just a reminder that these plots don't inform about treatment response heterogeneity on their own. Here's a plot of the treatment-control differences in energy expenditure from a crossover trial.

🙏 Simple tips for recording data in spreadsheets: statsepi.substack.com/p/simple-tip...

When you prepare a dataset to share with others, ask yourself: Will other people be able to fully understand this data and be able to use it accurately based on what I've provided to them?

"data doesn't lie" The reddest of red flags that someone is full to the brim of bullshit.

🍎 Can observational nutrition research provide causal evidence? ➡️In nutrition research, we often see that people who eat a certain way have different health outcomes. But does diet cause those outcomes? Not necessarily—correlation is not causation!

Periodic reminder the world of data analysis cannot be meaningfully categorised into "machine learning" and "statistics". Two cultures with substantial overlap in the use of methods (e.g. logistic regression), analytical goals (e.g. causal inference) and history jamanetwork.com/journals/jam...

Data management and sharing - Journal of Clinical Epidemiology www.jclinepi.com/article/S089...

Practical self-defense tip: when folks say "do your own research" about vaccines (for example), what they often mean is "go google studies, conducted using methods you are not trained to rigorously evaluate, that you can then use to reinforce your existing beliefs via a lot of confirmation bias."

Sincere kudos to the editors of the American Journal of Gastroenterology for publishing our letter (with @timpmorris.bsky.social). journals.lww.com/ajg/citation...

Still being able to find and access data from a project you worked on over 2 years ago -- Amazing. Being able to recreate all clean data files from the raw files without fail -- Priceless. Thank you organized file processes, thorough documentation, and reproducible #rstats scripts. 🙌

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

NEW PREPRINT! Enjoyed working with @tom-parks.bsky.social and @petedodd24.bsky.social on immortal time bias In its simplest form, ITB results from misallocation of person time, i.e. pre treatment time in intervention group being counted as time on treatment www.medrxiv.org/content/10.1... [1/n]

How do you ensure that your team is securely working with data? 1. Create policies that lay out how team members should access, work with, and store data. 2. Develop templates to be reused for common tasks. 3. Create style guides for naming/organizing things. 4. Store all of this in a team wiki.

Academics, let's make 2025 the year where we are more explicit and honest about our causal aims and interpretations Using, for instance, the terms "risk factor" or "associated with a decrease in" is not a clever way to avoid the issue

NEW PREPRINT A detailed overview of 32 popular predictive performance metrics for prediction models arxiv.org/abs/2412.10288