Scholar

Cyrus Samii

H-index: 28
Political science 26%
Mathematics 24%
cdsamii.bsky.social
👀 (given the remarkable robustness of BART as a static prediction method)
statme-bot.bsky.social
Christoph Breunig, Ruixuan Liu, Zhengfei Yu: Robust Semiparametric Inference for Bayesian Additive Regression Trees https://arxiv.org/abs/2509.24634 https://arxiv.org/pdf/2509.24634 https://arxiv.org/html/2509.24634

Reposted by: Cyrus Samii

statme-bot.bsky.social
Christoph Breunig, Ruixuan Liu, Zhengfei Yu: Robust Semiparametric Inference for Bayesian Additive Regression Trees https://arxiv.org/abs/2509.24634 https://arxiv.org/pdf/2509.24634 https://arxiv.org/html/2509.24634
cdsamii.bsky.social
Very well said. Re (2), a version of this is in the Korn and Graubard "Analysis of Health Surveys" textbook that explains how, under misspecification (and all models are somewhat misspecified), the weighted (population) fit is what we want rather than the sample fit.
polanalysis.bsky.social
Currently in FirstView: “Generalizing Trimming Bounds for Endogeneously Missing Outcome Data Using Random Forests." @cdsamii.bsky.social, Ye Wang, @jlzhou.bsky.social‬ present a partial identification approach that avoids strong assumptions. This is illustrated using a simulation and replication.
cdsamii.bsky.social
Agreed — nice round up of very well informed perspectives. I found Raleigh’s analysis especially convincing but all perspectives were thought provoking.
olihanney.bsky.social
Back to teaching or studying economics at university this September?

@voxdev.bsky.social has tons of useful resources for university economics courses - I have included some examples in this thread. 1/n
cdsamii.bsky.social
Skepticism toward vax and modern medicine is fairly widespread publicly as I’ve seen, and is tied up with antipathy toward “experts” (“do your own research” a la Aaron Rodgers), which universities embody. There is the woke issue sure, but there is also antipathy toward expertise to contend with.
cdsamii.bsky.social
Let’s take the area where there has been the most heat: vaccinations. The MRNA vax researcher doesn’t need to change what they do. It’s a problem of educating the public that this is useful stuff. The question is how to do that effectively.
cdsamii.bsky.social
Seems that a field that has taken an especially large hit in the current context is biomedical sciences, and this because, it seems, MAGA rejected the expert guidance on COVID. These rules leave many unanswered questions for that field, no?
cdsamii.bsky.social
I agree with comments here emphasizing Trump’s vengeance on the “medical establishment” after feeling that it conspired during COVID to unseat him. Would be nice if nurses and doctors generated a groundswell of alarm in their personal social networks about the dangers.
cdsamii.bsky.social
Montiel Olea has a few really nice papers on design from a decision theoretic perspective.
cdsamii.bsky.social
Anna Wilke and I have a paper (soon on Arxiv) that I can send on design diversification from minmax regret perspective. We were inspired by Manski and papers on experimental design like Banerjee et al. and Azevedo et al.

www.aeaweb.org/articles?id=...

www.journals.uchicago.edu/doi/abs/10.1...
University of Chicago Press Journals: Cookie absent
www.journals.uchicago.edu
cdsamii.bsky.social
(The tortured fit of a global polynomial)
cdsamii.bsky.social
For your weekend read I highly recommend this article on the Tampa Bay Rays and the thankless pursuit of excellence:

www.nytimes.com/2025/08/06/m...
Is He Baseball’s Most Brilliant Owner, or a Failure?
www.nytimes.com
cdsamii.bsky.social
👀
paperposterbot.bsky.social
link 📈🤖
A General Design-Based Framework and Estimator for Randomized Experiments (Harshaw, S\"avje, Wang) We describe a design-based framework for drawing causal inference in general randomized experiments. Causal effects are defined as linear functionals evaluated at unit-level potential outcom

Reposted by: Cyrus Samii

paperposterbot.bsky.social
link 📈🤖
A General Design-Based Framework and Estimator for Randomized Experiments (Harshaw, S\"avje, Wang) We describe a design-based framework for drawing causal inference in general randomized experiments. Causal effects are defined as linear functionals evaluated at unit-level potential outcom
cdsamii.bsky.social
We had a wee contribution on this for randomized experiments (cute by Abadie et al.). The idea extends by analogy to observational studies: cyrussamii.com/wp-content/u...
cyrussamii.com
cdsamii.bsky.social
One observes only a sample of the potential outcomes. Sampling error based standard errors provide for conservative inference for such uncertainty. Surprisingly, this was not widely known until fairly recently. (Cf the Abadie et al paper and refs therein.)

Reposted by: Cyrus Samii

nber.org
Using new tools in legal language processing to show workers value the legal rights provided by collective bargaining agreements, from Benjamin W. Arold, Elliott Ash, W. Bentley MacLeod, and Suresh Naidu https://www.nber.org/papers/w33605

Reposted by: Cyrus Samii

paperposterbot.bsky.social
link 📈🤖
Finite Population Identification and Design-Based Sensitivity Analysis (Kline, Masten) We develop an approach to sensitivity analysis that uses design distributions to calibrate sensitivity parameters in a finite population model. We use this approach to (1) give a new formal analysis of

Reposted by: Cyrus Samii

miguelhernan.org
If you're wondering about differences between publicly-funded research in non-profit universities and
privately-funded research in for-profit companies, watch this:
www.youtube.com/watch?v=Ar0z...

The topic is the "de-extinction of the dire wolf", but the message applies beyond it. (Think "AI".)
They Didn't Make Dire Wolves, They Made Something…Else
YouTube video by hankschannel
www.youtube.com

Reposted by: Cyrus Samii

paperposterbot.bsky.social
link 📈🤖
Design-based Estimation Theory for Complex Experiments (Chang) This paper considers the estimation of treatment effects in randomized experiments with complex experimental designs, including cases with interference between units. We develop a design-based estimation theory for arbitrary e
thomvolker.bsky.social
After two weeks, I'm finally done!

In this post, I explain different approaches for solving linear regression in R: directly, using QR, singular value and Cholesky decompositions, and do some benchmarking for comparison with in-built approaches.

thomvolker.github.io/blog/2506_re...

References

Fields & subjects

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