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Statistical Modeling, Causal Inference, and Social Science

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Posts

Reading like it’s 1937

Hey Philip Larkin, I don’t get what you were saying here!

Even the easiest data requests can require some effort

Assistant professor positions at USI in Lugano

David Owen writes about hearing aids

Was Admiral Poindexter a terrorist? (Who’s in charge of your prediction market?)

Here’s a statistics research project for you: Is the skewness of the distribution of the empirical correlation coefficient asymptotically proportional to the correlation?

Survey Statistics: individualism doesn’t work

Sabbatical and pre-faculty positions at Flatiron Institute in NYC

Reanalysis of that Nobel prizewinning study of patents and innovation

Bayesian probability, like frequentist probability, is a model-based activity that is mathematically anchored by physical randomization at one end and calibration to a reference set at the other

Collective sensemaking event in NYC, October 26

Aversive statistical methods explain differences in “dark” publication in PNAS across subject areas

The war on data, 2025 edition

Separating the whack from the chaff in critiques of decision theory

The importance of essentialism in children’s and adults’ conceptions of the world

Generalizing Treatment Effects from Trials to EHR Populations (Qixuan Chen’s talk this Tues morning)

“All Our Default Models Are Wrong: Causal inference for varying treatment effects”: my talk this Saturday morning in Ottawa

Questions about statistical claims in paper from recent Nobel prize winners; some general challenges in trying understand nonlinear patterns using quadratic regression

Survey Statistics: MRPW

Stockholm Syndrome

StanCon 2026 in Uppsala, Sweden

“The Impossible Man”: Patchen Barss’s biography of Roger Penrose

This is what a degree in cannabis studies will get ya

7 reasons to use Bayesian inference!

Columbia fake U.S. News statistics update: They paid $9 million and are still, bizarrely, refusing to admit misreporting of data, even though everybody knows they misreported data.

The worst research papers I’ve ever published

Prior distributions for regression coefficients

Selection bias in junk science: Which junk science gets a hearing?

Aki looking for a doctoral student to develop Bayesian workflow

Survey Statistics: struggles with equivalent weights

Historical American Political Finance Data at the National Archives

“300 Paintings”

When rich people believe, or pretend to believe, stupid things (tennis edition)

Uncanny academic valley: Brian Wansink as proto-chatbot

Unusual consulting request

It’s a JAX, JAX, JAX, JAX World

Adding noise to the data to reduce overfitting . . . How does that work?

“It’s horrible that they’re sucking young researchers into this vortex. It’s Gigo and Gresham all the way down.”

Yes, your single vote really can make a difference! (in Canada)

Survey Statistics: beyond balancing

“Dangerous Fictions” and the norm of entertainment

Behind-the-Scenes Seminar on social science this Fri 3 Oct

Game theory corner: did Eric Adams play his hand well? (It’s a little like Murder on the Orient Express, it’s a little like The Sting.)

“Veridical (truthful) Data Science”: Another way of looking at statistical workflow

In music, literature, and technical writing, the relation of large-scale structure to the local action

A Selective History of Political Polling and Election Forecasting

The Dodgers are hiring

“On the poor statistical properties of the P-curve meta-analytic procedure”

More on the decline and fall of Steven Levitt

Survey Statistics: Fat Bear Week

Bridging prediction and intervention in social systems

World’s greatest 404 page

Protecting data from the public and ourselves

It’s JAMA time, baby! Junk science presented as public health research

Who gets listed first on a collaborative article or book?

Monty Hall and generative modeling: Drawing the tree is the most important step

When thinking about causal inference, mechanistic or process models are important. I think that the association of “causal” with black-box models leads to lots of problems.

Condition numbers for HMC and the funnel

More Howl, after Allen Ginsberg for the AI-headed hipsters

“Why probability probably doesn’t exist (but it is useful to act like it does)”

The Miami Marlins are hiring

Hey, Nature magazine! Reputation is a two-way street.

Survey Statistics: random sampling is not leaving

Stats and ML postdoc and permanent hiring season officially open at Flatiron

Softverse: Auto-compute Citations to Software From Replication Files

The Desperation of Causal Inference in Ecology

Princeton Consumer Research reports a 93.94% success rate . . . not quite as good as Harvard, which gets you to “statistically indistinguishable from 100%”!

Helen DeWitt says, “programming occupies a place similar to that of literacy in mediaeval England.”

BDA3 for free

Draw it with your eyes closed: the art of the statistics assignment

That external validity question: How to think about a 3-year UBI study?

Hot social science topics 20 years ago and hot social science topics now

Howl, after Allen Ginsberg (for the AI-headed hipsters)

Going beyond naive individualistic models of social science

Survey Statistics: Imputation II

Show, don’t tell: ChatGPT 5 marginalizing Gelman’s measurement error model in Stan

Hypertext as constructed and hypertext as read

You learn about possible plagiarism in a literary work. How does that affect your view of it? (The A. J. Finn story)

This post is not about Newt Gingrich and Fox news, nor is it about Michio Kaku and string theory.

Weighting of evidence and conflict of interest at the FDA and elsewhere

Experimentation and thinking at the level of a program of experiments

Generate but verify: Reconciling the evidence utility of chatbots in many settings with chatbots’ evident lack of understanding

Blogging’s a great way to express your ideas.

“Assembling an unbiased jury”?