yiqingxu
- Reposted by yiqingxuA blog post giving a more thorough take on survey experiments and the credibility revolution: cyrussamii.com?p=4168
- Preliminary. Comments are welcome!
- New paper! @william-dinneen.bsky.social @guygrossman.bsky.social Yiqing Xu and I use GPT to code 91k articles from 174 polisci journals (2003–2023)and track research designs, transparency practices, and citations. How has the credibility revolution reshaped the discipline? doi.org/10.31235/osf... 🧵
- Thrilled to share that **fect** has won the 2025 Best Statistical Software Award from the Society of Political Methodology. We're honored! polmeth.org/statistical-... To celebrate, we've just released fect v2.0.5 on CRAN & Github 🎉
- In this new version, we fixed many bugs and introduced more features. Check it out: yiqingxu.org/packages/fect/ Special thanks to Ziyi, Rivka, and Tianzhu for their incredible work and dedication. More features are on the way!
- We also highlighted the need to use the leave-one-out approach to obtain pretrend estimates, thanks to Zikai and Anton's cautionary note: osf.io/ngr3d_v1/ @astrezh.bsky.social
- Honored by this recognition!
- We are pleased to announce the 2025 Editors’ Choice Award for the paper “How Much Should We Trust Instrumental Variable Estimates in Political Science? Practical Advice Based on 67 Replicated Studies” by @apoorvalal.com, @maclockhart.bsky.social, @yiqingxu.bsky.social, and @garyzu.bsky.social.
- Glad this paper is finally out in @apsrjournal.bsky.social, five years after we began the project. Hope it proves useful to researchers. www.cambridge.org/core/journal... Software support: yiqingxu.org/packages/fec...
- As a Chinese immigrant living in the U.S., I have witnessed declines in optimism purely due to the drastic erosion of existing institutions—first around 2015 in my home country, and now, in 2025, in the United States. It's devastating.
- Draft “A Practical Guide to Estimating Conditional Marginal Effects: Modern Approaches” is on arXiv: arxiv.org/pdf/2504.01355 w/ two amazing grad students, Jiehan_Liu & Ziyi Liu 🧵
- 2/ We prepared it for Cambridge Element & previewed parts of it in our response to a blog post last month. Scholars are often interested in how treatment effects vary with a moderating variable (example below). We hope this will serve as a useful reference for this common task down the road.
- 3/ We start by defining the estimand, the CME, and presenting main identification results in the discrete-covariate case. We then review & improve the semiparametric kernel estimator. The improvements include fully moderated models, adaptive kernels, and uniform confidence intervals.
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View full thread7/ We have prototypes for all the algorithms used in the Element and will soon roll them out in **interflex** for R. Comments and suggestions are more than welcome!
- I woke up at 5:30 a.m. today, and the first thing on my mind was Stefan Zweig’s The World of Yesterday: Memoirs of a European, a book I loved as a child. His despair stuck with me and feels especially relevant now.
- Reposted by yiqingxu"The bottom 80% of earners spent 25% more than they did four years earlier, barely outpacing price increases of 21% over that period. The top 10% spent 58% more." www.wsj.com/economy/cons...
