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Done another semester teaching causal inference🙂. Updated my course slides, added survival data, labs, corrected more typos this time. Close to 800 pages now. Always more to update next year.
www2.stat.duke.edu/~fl35/CausalIn…
Fan Li
55 posts
Fan Li
@FanLiDuke
Professor@Duke, Statistician, Data Scientist, Causal Inference researcher
Durham, NC, USA
Joined March 2024
- Twitter academia: 1. I am happy to announce xx (whatever trivial) 2. I am thrilled/excited that xx (papers, grants, promotion) 3. I am honored that xx ("awards" in all senses) Adding to that list now: "How I publish xx papers in x years" What next? How I become god?
- Hands-down the best textbook for causal inference.excited to see the physical copy of the book; nervous about the potential errors. Comments are welcome.
- Lack of general code is one main barrier to Bayesian causal inference. Peng Ding gave some simple Stan code and intro slides on Bayesian causal inference based on our review paper. A long version is here: www2.stat.duke.edu/~fl35/teaching…Just gave a guest lecture on Bayesian Causal Inference at Williams College, with slides and R code at doi.org/10.7910/DVN/JO… which is an introduction to our review paper royalsocietypublishing.org/doi/10.1098/rs… @fabri_mealli @FanLiDuke (I never taught any Bayesian Statistics at Berkeley.)
- Happy to see my paper with @pengding00 and Anqi Zhao @DukeU "Covariate adjustment in randomized experiments with missing outcomes and covariates" is out doi.org/10.1093/biomet… This 8-pages paper gives a simple and clean solution to a prevalent practical problem.
- Another great book draft (on linear models) from Peng Ding @pengding00. Clean, clear, and concise. Very up-to-date.[Download 400-page PDF eBook] Linear Models in #MachineLearning and Statistical Learning: arxiv.org/abs/2401.00649 ————— #Mathematics #DataScience #LinearAlgebra #Statistics
- Replying to @MarvinSchmittMLand of course, wanting the whole world to know "I am humbled"
- Replying to @francoisfleuretNo model is causal, assumptions make it "causal." Blame the abuse of the name "causal model" and the lack of assumption checking instead.
- Excellent point. Serving as the editor for Social Science, Biostatistics, Policy at Annals of Applied Statistics, I have spent countless hours reviewing papers, burned social capitals, offending many authors (rejecting their papers). My stipend? 0. Is the system sustainable?I am honored to be offered the job of Editor-in-Chief of Health Economics @HECJournalTweet, replacing the excellent Sally Stearns (@GillingsGlobal). I plan to reject this offer. Why?
- Replying to @economeager"How I become god" is a even better click bait than "(non econ) how I write xx papers in x years” or "(econ) how I write one paper in less than 10 years."
- Good stat joke. Once in a party, the late Susie Bayarri (one of the great Bayesians) and a few of us were discussing who is the statistician divorced the most times. Susie said: "He must be a frequentist!"
- Replying to @5_utrReality is, even the best designed RCT, at the time of completion, looks more like observational studies, because of, e.g. unintentional and uncontrolled intercurrent events. The blanket hostility to obs studies is unwarranted and a dis-service
- Saw many cicada shells everywhere lately. Turned out two different broods of cicadas (one on a 13 yr and other on a 17 yr cycle -- two prime numbers) emerge at the same time from underground this year, first time since 1803, next time? 2024+17X13=2245.
- Brilliant strike back. I was compelled to google who Genc is.The peer review process.
