Fan Li

Professor@Duke, Statistician, Data Scientist, Causal Inference researcher

[Fan Li @FanLiDuke]

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.
https://t.co/Bpy7uYRKVq

[Fan Li @FanLiDuke]

Try our new online calculator for sample size and power calculations for causal inference in observational studies, e.g. target trial emulation, which turns out to be simple -- only requiring two inputs besides the standard RCT inputs.
https://t.co/6tC31hY6io

[Fan Li @FanLiDuke]

I was often asked by practitioners about power calculations for causal inference with observational data, a hard problem with little leads. Finally had a clean solution, thanks to my spectacular student Bo Liu. Here it is:
https://t.co/r2nL9kTQ55

https://t.co/G077LDdG2Z

[Fan Li @FanLiDuke]

@sasilu6 What's wrong with lecture notes? This gives the most concise, update-to-date and complete survey of the field, with examples, HWs, codes. Any other book on market offers these?

[Fan Li @FanLiDuke]

Hands-down the best textbook for causal inference.

[Peng Ding @pengding00]

excited to see the physical copy of the book; nervous about the potential errors. Comments are welcome.

[Fan Li @FanLiDuke]

@signalvoyager @Andrew_Akbashev Often it is not an award but rather trivial self recognition.

[Fan Li @FanLiDuke]

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?

[Fan Li @FanLiDuke]

@ssprickschuster Except that often "I am humbled/honored" is a simply thin-veiled bragging of trivial things or openly flattering relevant people (e.g. potential reviewers or letter writers)

[Fan Li @FanLiDuke]

@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."

[Fan Li @FanLiDuke]

@MarvinSchmittML and of course, wanting the whole world to know "I am humbled"

[Fan Li @FanLiDuke]

@chefjeffsf Except that Panda Express is not Chinese, it is safely American.

[Fan Li @FanLiDuke]

@f2harrell @PWGTennant great idea, will adopt later.

[Fan Li @FanLiDuke]

@BhramarBioStat Second this. Learning some history of statistics (started from survey sampling) also helps.

[Peng Ding @pengding00]

This is an interesting and useful trick. However, centering factors has some special restrictions on the estimated factorial effects when there are more than 3 factors (3 is the magic number there!). This motivates us to write this paper: https://t.co/Y94bGAN28V

[Fan Li @FanLiDuke]

@gv_lazcano @5_utr I am not saying one should go to obs studies. I am saying, to analyze your holy grail RCTs properly, many causal inference techniques designed for observational studies are necessary. Again, blanket hostility is counter-productive.

[Fan Li @FanLiDuke]

@lhan320 So sorry for your loss

[apoorva.lal @Apoorva__Lal]

what a vote of confidence [cc @pengding00 ]

[Fan Li @FanLiDuke]

@yudapearl @f2harrell @soboleffspaces @stephensenn @PWGTennant There is a subtle technical difference between the three versions of ATE, but I don't believe the technical purity of PATE and SATE makes them more superior. In practice, the numerical difference is little - that matters the most.

[Fan Li @FanLiDuke]

@f2harrell @yudapearl @soboleffspaces @stephensenn @PWGTennant CATE is a different animal, fundamentally you lack data to estimate infinite number of CATEs, of course the uncertainty is bigger. I don't think you can get a good sample CATE in general.

[Fan Li @FanLiDuke]

@f2harrell @yudapearl @soboleffspaces @stephensenn @PWGTennant In fact, most CI practitioners estimate a third estimand, a mix of PATE and SATE, because of the conditioning on the X in the sample. My Bayesian causal review paper carefully discussed this. In practice, diff between P-, S-, M- ATE is small, not warrant much concern