Reposted by Mikail NourredineRichard Riley (R²) @richarddriley.bsky.social · 16/02/2026⭐ NEW PAPER ⭐ on a Bayesian approach to sample size calculations for external validation of risk prediction models - account for uncertainty in the assumed true performance of the model - plus calculate assurance probabilities & the value of information onlinelibrary.wiley.com/doi/10.1002/... 03411
Reposted by Mikail NourredinePausal Zivference @pausalz.bsky.social · 27/12/2024That led to this paper which was accepted in JRSSA. In it, I make the Epidemiology paper a bit more formal, extend to continuous covariates, proposed two new AIPW estimators, and provide a new illustrative example academic.oup.com/jrsssa/advan...academic.oup.comSynthesis estimators for transportability with positivity violations by a continuous covariateAbstract. Studies intended to estimate the effect of a treatment, like randomized trials, may not be sampled from the desired target population. To correct 243
Reposted by Mikail NourredinePausal Zivference @pausalz.bsky.social · 27/12/2024The first paper on using a mathematical model to fill in nonpositive regions was published in Epidemiology in the January issue. This paper lays out the basics in the case of nonpositivity by a binary variable and we proposed IPW and g-computation estimators journals.lww.com/epidem/abstr...journals.lww.comTransportability Without Positivity: A Synthesis of... : Epidemiologyn a positivity assumption, such that all relevant covariate patterns in the target population are also observed in the study sample. Strict eligibility criteria, particularly in the context of randomi... 272
Reposted by Mikail NourredineMiguel Hernan @miguelhernan.org · 23/12/2024Upgrade your #causalinference arsenal. A revision of our book "Causal Inference: What If" is available at miguelhernan.org/whatifbook Thanks to everyone who suggested improvements, reported typos, and proposed new citations and material. Enjoy the #WhatIfBook plus code and data. Also, it's free. 10373113
Reposted by Mikail NourredineGaël Varoquaux @gaelvaroquaux.bsky.social · 19/12/2024People: please don't ML for the sake of ML. I keep seeing manuscripts using fancy machine learning on brain-imaging data, where, in my opinion (having processed a lot of brain-imaging data), the method is way too complex for the richness of the data. Fancier is not better per se 58815
Reposted by Mikail NourredineClémence Leyrat @clemley.bsky.social · 18/12/2024📣 Do you want to learn about recent advances in causal inference? Colleagues at INSERM are organising a workshop gathering international experts in the field. Bonus: it's happening in two amazing locations 🌇🇫🇷 188