I've long held that p-values/NHST should be banished. I've written some bits and pieces on it in the past, but have finally written a full essay. Please take a look and comment, matloff.github.io/No-P-Values

#statstab #340 How to interpret and report nonlinear effects from Generalized Additive Models Thoughts: Maybe you heard about GAMs and spline, but not sure how to use them. Here's a #R tutorial. #GAM #spline #nonlinear #tutorial #guide #marginaleffects ecogambler.netlify.app/blog/interpret…

Finally got around to incorporating all Github feedback on my open access textbook, making around 20 minor improvements, and updating some references. 17 chapters of state of the art stats and methods education, freely available for any course you teach. lakens.github.io/statistical_in…

Risk Ratios vs. Odds Ratios: Which to Use & WHY (Clearly Explained 💪) youtu.be/EmaMo8A4Upc #rstats #statistics #dataanalysis #stats #datascience #r4ds #tidymodels

📊I've uploaded the 3rd stats lab post: "What is the Logic Behind a Two-Way Fixed Effects Analysis?" It includes the meaning of control unit or/and time fixed effect with graphs and R codes. idlhy0218.github.io/page%20buildin… #rstats #econtwitter #soctwitter #dataviz

For the new kids in back: If you hate statistics, you'll love my free lectures. Putting science before statistics, from basics of inference & causal modeling to multilevel models & dynamic state space models. It's all free, made with love and sympathy. youtube.com/playlist?list=…

Difference-in-differences for practitioners from the diff-in-diffs dream team!

ICYMI - our new paper explaining how small sample sizes negatively impact the quality and performance of clinical prediction models in AI-based healthcare

If you're looking to get up to speed fast on data engineering and analytics, then here are ten free articles and videos you're going to want to check out. 1. How To Data Model – Real Life Examples Of How Companies Model Their Data theseattledataguy.com/how-to-data-mo… 2. Data Engineers Vs

We have a new post, and as the title says, it's all about heterogeneous treatment effects :) Because not everyone responds to treatment the same way, and our methods should reflect that substacktools.com/sharex/O2tQdSh9

#statstab #382 The JASP Guidelines for Conducting and Reporting a Bayesian Analysis Thoughts: JASP Statistics is often people's first attempt at Bayesian statistics. But proper inference and reporting is crucial. #JASP #Bayesian #BayesFactor #guide #tutorial link.springer.com/article/10.375…

One of my favorite papers in recent years included this diagram. It shows the impact of controlling for three different types of variables: confounders, colliders, and mediators. With confounders, control is good. With the others, you ruin your result by controlling.

New paper in BMJ (Research Methods & Reporting): “Dealing with continuous variables and modelling non-linear associations in healthcare data: practical guide” led by Pedro Lopez-Ayala & Tobias Zimmermann with Gary Collins & myself bmj.com/content/390/bm…

New and improved version of our Estimating Causal Effects paper: arxiv.org/pdf/2508.02310

Many ask themselves, «Why would I use a semantic layer? How to build one?». But a better question is: How many times have you implemented the same revenue calculation differently across your company's dashboards, reports, and apps? This is why semantic layers exist.

Many researchers overlook or misinterpret statistical assumptions. Misunderstanding these assumptions can lead to using the wrong statistical tests, drawing inaccurate conclusions, and weakening a study’s credibility. Even common analyses can produce misleading results if their

If you are preparing your bachelor statistics course and would like to add optional material for students to better understand statistics on a conceptual level (see topics in the screenshot) my free textbook provides a state of the art overview. lakens.github.io/statistical_in…

Head Of Data: "AI won’t save us until we fix our data infrastructure and quality" CEO: "Ok… but we still put ‘AI’ on our Q4 roadmap right?"

Found this old, Excel-based surface plot of the relationship between sample size, effect size, and p-values. Should I remake this in R? 🤔

📚 In summer 2023, my book Causal Analysis was published with The MIT Press @mitpress.bsky.social. Just two years later😉 I’m very happy to share that the lecture slides are now freely available in both PDF and LaTeX (as zip files), along with the datasets and R/Python code: 👉 unifr.ch/appecon/en/res…