Mathias Weis Damkjær
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tweis.bsky.social
Mathias Weis Damkjær
@tweis.bsky.social
31 followers 86 following 2 posts
MD, PhD Student at Centre of Evidence-Based Medicine, Cochrane/Denmark.
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Reposted by Mathias Weis Damkjær
avehtari.bsky.social
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)
**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
January 26, 2026 at 8:18 AM
Reposted by Mathias Weis Damkjær
stephensenn.bsky.social
"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
November 24, 2025 at 12:01 PM
Reposted by Mathias Weis Damkjær
marionkcampbell.bsky.social
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
August 18, 2025 at 6:35 AM
Reposted by Mathias Weis Damkjær
yangbd.bsky.social
❓ 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
June 13, 2025 at 9:27 AM
Reposted by Mathias Weis Damkjær
wviechtb.bsky.social
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
2025 - ESMARConf
esmarconf.org
March 6, 2025 at 8:45 AM
Reposted by Mathias Weis Damkjær
andershuitfeldt.net
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...)
Should one derive risk difference from the odds ratio?
I urge all readers of this thread to read the excellent new preprint from philosopher of science Veli-Pekka Parkkinen, “Choice of effect measure, extrapolation, and decision-making in patient care an...
discourse.datamethods.org
February 26, 2025 at 10:00 AM
Reposted by Mathias Weis Damkjær
statsepi.bsky.social
Two angels discussing the basics of treatment effects.

(ICYMI)

statsepi.substack.com/p/a-conversa...
A conversation on treatment effects
The trial statistician and the clinical investigator took a step back to admire their creation.
statsepi.substack.com
January 9, 2025 at 8:15 AM
Reposted by Mathias Weis Damkjær
jdwilko.bsky.social
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...
Giant study finds untrustworthy trials pollute gold-standard medical reviews
Two-year collaboration aims to create tools to help counter the tide of flawed research.
www.nature.com
December 19, 2024 at 9:34 AM