Andy going thru the epstein files taking multiple killshots including at his own longtime coauthors............ incredible. posting in case you (like me) missed it
statmodeling.stat.columbia.edu/2026/01/31/f...
**Part 1: From Bayesian inference to Bayesian workflow** 1. Bayesian theory and Bayesian practice 2. Statistical modeling and workflow 3. Computational tools 4. Introduction to workflow: Modeling performance on a multiple choice exam **Part 2: Statistical workflow** 5. Building statistical models 6. Using simulations to capture uncertainty 7. Prediction, generalization, and causal inference 8. Visualizing and checking fitted models 9. Comparing and improving models 10. Statistical inference and scientific inference **Part 3: Computational workflow** 11. Fitting statistical models 12. Diagnosing and fixing problems with fitting 13. Approximate algorithms and approximate models 14. Simulation-based calibration checking 15. Statistical modeling as software development
**4. Case studies** 16. Coding a series of models: Simulated data of movie ratings 17. Prior specification for regression models: Reanalysis of a sleep study 18. Predictive model checking and comparison: Clinical trial 19. Building up to a hierarchical model: Coronavirus testing 20. Using a fitted model for decision analysis: Mixture model for time series competition 21. Posterior predictive checking: Stochastic learning in dogs 22. Incremental development and testing: Black cat adoptions 23. Debugging a model: World Cup football 24. Leave-one-out cross validation model checking and comparison: Roaches 25. Model building and expansion: Golf putting 26. Model building with latent variables: Markov models for animal movement 27. Model building: Time-series decomposition for birthdays 28. Models for regression coefficients and variable selection: Student grades 29. Sampling problems with latent variables: No vehicles in the park 30. Challenge of multimodality: Differential equation for planetary motion 31. Simulation-based calibration checking in model development workflow **Appendices** A. Statistical and computational workflow for Bayesians and non-Bayesians B. How to get the most out of Bayesian Data Analysis
Bayesian Workflow by
Andrew Gelman, Aki Vehtari, @rmcelreath.bsky.social with @danpsimpson.bsky.social, @charlesm993.bsky.social, @yulingy.bsky.social, Lauren Kennedy, Jonah Gabry, @paulbuerkner.com, @modrakm.bsky.social, @vianeylb.bsky.social
(in production, estimated copy-editing time 6 weeks)
"we probably do not need to worry about the fact that the actual effect of one treatment rather than the other is not the same for all patients. Quite limited knowledge about an average improvement is the best that we can do" John Tukey, Controlled Clinical Trials, 1993 p282
There has been a lot of debate recently about the promise of real world data - the routine (observational) data collected on patients eg treatments received, clinical outcomes etc – for estimating treatment effects. But can they deliver? 1/9
#MethodologyMonday #123
❓ In people with HIV, is using two different rapid tests together ('parallel testing') to diagnose TB more accurate than using only one?
An 'incremental' accuracy question: few Cochrane Reviews have yet addressed such questions.
Adult review: shorturl.at/r9CUG
Child review: shorturl.at/nSosK
The Evidence Synthesis and Meta-Analysis in R Conference (ESMARConf) is back! It will be held June 11th to the 13th, 2025: esmarconf.org/2025/
Recordings of the talks and workshops from previous years can be found here: esmarconf.org/recordings/
#ESMARConf #MetaAnalysis #EvidenceSynthesis #RStats
After two years of trying to avoid this discussion, I just necroed *that thread* on datamethods (discourse.datamethods.org/t/should-one...) in order to share an excellent preprint by philosopher Veli-Pekka Parkkinen (philsci-archive.pitt.edu/24785/1/efme...)
Two angels discussing the basics of treatment effects.
(ICYMI)
statsepi.substack.com/p/a-conversa...
Thanks for making this freely available. It is a great book.
Nice write up of our study applying potential trustworthiness checks to RCTs in 50 Cochrane Reviews in Nature by @richvn.bsky.social : www.nature.com/articles/d41...
Nice and important work!