When I reflect on what shaped me most as a scholar, one seminar stands out: Ruth Collier’s dissertation writing workshop at Berkeley. I wrote about its influence on my research, teaching, and scholarship in general. jaeyeonkim.substack.com/p/the-ruth-c...

Good news everyone 🥳 Our (w @vincentab.bsky.social) primer on models as prediction machines (with the marginaleffects package) is finally officially published!> journals.sagepub.com/doi/10.1177/...

Journal editors - the status quo on preregistration is not working! You need to check submissions vs. preregistrations before sending articles out for review. *56%* of experiments I reviewed in last year have severe problems with non-disclosure, undocumented deviations, & more - see Claude summary ↓

You guys @carlislerainey.bsky.social has a free textbook online and it seems really useful pos5747.github.io/notes/

Bilingual joke? French Wikipedia says the Poisson distribution is "not to be confused with Fisher's distribution" (the F-distribution) fr.wikipedia.org/wiki/Loi_de_...

Rosenbaum's Observation and Experiment is great too. I have sadly not read his more technical books yet. www.hup.harvard.edu/books/978067...

You need to bring in the same toolkit as in studies that try to establish causality without randomization. I know it sounds unfair, but I don’t make the rules. These situations are instances of post-treatment bias, if you want to read up on it as a psychologist:

Speaking truth to power

A more user friendly t-test regression variable description frequency plots, and more. datacolada.org/132

🚨SOLUTIONS🚨 Desk reject more stuff with actionable feedback. Don’t request second reviews Build larger editorial boards of volunteers Wait to submit your work until it’s ready; a.k.a don’t send in your half-baked trash hoping for feedback 6/7

After years in academia, I’m exploring data science and research roles in industry. I'm a quant. social scientist (PhD Yale ’24, NYU) focused on causal inference, experiments, and large-scale data. Feel free to get in touch or share; all leads appreciated. [email protected]

This quote also reminds me of something that we wrote in our paper on path analysis (journals.sagepub.com/doi/10.1177/...). People are just expecting *way* too much of a single study, literally new discoveries exceeding Gregor Mendel's.

Comparing registrations to published papers is essential to research integrity - and almost no one does it routinely because it's slow, messy, and time-demanding. RegCheck was built to help make this process easier. Today, we launch RegCheck V2. 🧵 regcheck.app

“Coding for humans: Best practices for writing software people can read” statmodeling.stat.columbia.edu/2026/01/17/c...

Accessibility is *absolutely* key but also hard because of the curse of knowledge. I've written down some writing advice here: www.the100.ci/2024/12/01/w.... If you're more of a technical person, consider teaming up with a substantive researcher for instant audience access.>

Some people bring up (1) the cost of criticism and (2) that a lot of criticism has already been voiced but ignored. Both points are valid, so here are some suggestion for (1) reducing backlash and (2) increasing impact (from this talk of mine: juliarohrer.com/wp-content/u...

Some closing thoughts for my students this semester on LLMs and learning #rstats datavizf25.classes.andrewheiss.com/news/2025-12...

Gentle reminder that a correlation coefficient isn’t a particularly great way to quantify the effect of a dichotomous treatment. See also www.the100.ci/2025/07/28/w...

Excellent new editorial and guideline on interpreting p values and interval estimates bjsm.bmj.com/content/earl...

Are you or one of your students considering doing a Ph.D. in a social science? I've spent a lot of time talking about this w/ students & finally wrote something up. IMO, there are only 3 good reasons to do it. One of them needs to be true--otherwise, don't. medium.com/the-quantast...

A nice recent article on why you should abandon hazard ratios. #statssky #episky

See our No-Spin report on a widely-covered NBER study of Medicaid expansion. In brief: Despite the abstract's claims that expansion reduced adult mortality 2.5%, the study found much smaller effects that fell short of statistical significance in its main preregistered analysis.🧵

Starting to look like I might not be able to work at Harvard anymore due to recent funding cuts. If you know of any open statistical consulting positions that support remote work or are NYC-based, please reach out! 😅

Issues with interpreting p-values haunts even AI, which is prone to same biases as human researchers. ChatGPT, Gemini & Claude all fall prey to "dichotomania" - treating p=0.049 & p=0.051 as categorically different, and paying too much attention to significance. www.cambridge.org/core/journal...

NEW: CONSORT 2025 now published! Some notable changes: -items on analysis populations, missing data methods, and sensitivity analyses -reporting of non-adherence and concomitant care -reporting of changes to any study methods, not just outcomes -and lots of other things www.bmj.com/content/389/...

How to write a response to reviewers. www.sciencedirect.com/science/arti...

Very nice explainer by @economictricks.bsky.social www.econometrics.blog/post/why-eco...

today we will all read imbens 2021 on statistical significance and p values, which is a strong contender for having the best opening paragraph of any stats paper pubs.aeaweb.org/doi/pdf/10.1...

Here's some older, related stuff (from me) aimed at political scientists. Related paper #1 "Arguing for a Negligible Effect" Journal: onlinelibrary.wiley.... PDF: www.carlislerainey.c...

"The Need for Equivalence Testing in Economics" from Jack Fitzgerald (@jackfitzgerald.bsky.social) Preprint: osf.io/preprints/met... We know that "not significant" does not imply evidence for "no effect," but I still see papers make this leap. Good to see more work making this point forcefully!

An important plea from @lizstuart.bsky.social in today's SCI-OCIS Special Webinar Series:

Good thread. I will add, another disadvantage of the current system of opacity is a great deal of interesting thought + work in referee reports is highly underutilized (never read by anyone other than author + editor)

Because I've seen the law of iterated expectations, Jensen's inequality, and the central limit theorem mentioned in the past few days, I'll migrate one of my early Twitter posts about the tools necessary to master econometrics -- which includes each of those. Here it is.

I quite like this platform, but it would be even better if we had: - bookmarks - DMs - polls

David Aldous made a similar point: www.stat.berkeley.edu/~aldous/Blog...

3. Find a mentor who supports you, but also pushes you in ways that work for you. There are many ways to be a good supervisor, and not every style works for every person. Find someone who's style works for you.

@lmiratrix.bsky.social is now on Bluesky!