Statistical Modeling, Causal Inference, and Social Science

Statistical Modeling, Causal Inference, and Social Science

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Academic statistics blog frequently addressing clinical trial design/causal inference and evidence appraisal.

An Economist Writes:  “The Fulminations over the #1 Pick Seem Overheated to Me.”
NewsMay 3, 2026

An Economist Writes: “The Fulminations over the #1 Pick Seem Overheated to Me.”

Economist Jonathan Falk argues that the hype surrounding the #1 draft pick is overstated. He notes that assessment errors and the prevalence of busts compress the expected advantage over the #2 slot. Falk also stresses that team fit and positional...

By Statistical Modeling, Causal Inference, and Social Science
Show Me Science
NewsApr 29, 2026

Show Me Science

The piece argues that AI reviewers, especially large language models, are reshaping scientific publishing by treating papers as data sources rather than narrative summaries. It notes a growing call for “show me” guidelines—plots, raw outputs, prompts, and failure cases—to replace...

By Statistical Modeling, Causal Inference, and Social Science
If that CDC Report Had Just Included some Fake Citations and some Crazy Dietary Advice, the Boss Would Surely Have...
NewsApr 22, 2026

If that CDC Report Had Just Included some Fake Citations and some Crazy Dietary Advice, the Boss Would Surely Have...

The acting head of the CDC canceled a study that found Covid‑19 vaccines cut emergency‑room visits by 50% and hospitalizations by 55% during the last winter. The research, cleared by agency scientists, was slated for the Morbidity and Mortality Weekly...

By Statistical Modeling, Causal Inference, and Social Science
Fraud and the False Optimism of AI for Science
NewsApr 22, 2026

Fraud and the False Optimism of AI for Science

The article debates whether AI‑generated research constitutes fraud or a legitimate productivity tool. It contrasts optimistic views that see AI as a natural extension of scientific methods with pessimistic concerns that outsourcing idea generation erodes judgment and misattributes credit. The...

By Statistical Modeling, Causal Inference, and Social Science
“Making Your Research Free May Cost You”
NewsApr 18, 2026

“Making Your Research Free May Cost You”

The NIH’s new policy, effective July 1, requires that all research funded by the agency be made freely and immediately available, eliminating the previous one‑year embargo. Major for‑profit publishers such as Springer Nature and Elsevier have responded by making open‑access article‑processing...

By Statistical Modeling, Causal Inference, and Social Science
The Bayesian Workflow Book Is Coming!
NewsApr 16, 2026

The Bayesian Workflow Book Is Coming!

Statistical pioneers Andrew Gelman, Aki Vehtari, Richard McElreath and colleagues have announced the upcoming release of “Bayesian Workflow,” a new textbook that expands on the classic “Bayesian Data Analysis” by adding practical guidance on model building, computation, and validation. The...

By Statistical Modeling, Causal Inference, and Social Science
“The FTC Does Not Have Our Backs, that Much Is Clear”
NewsApr 11, 2026

“The FTC Does Not Have Our Backs, that Much Is Clear”

The FTC reached a settlement with Match Group’s OKCupid over the app’s undisclosed sharing of user photos with facial‑recognition firm Clarifai. The agreement imposes a permanent ban on misrepresenting data practices but carries no monetary penalty, despite executives holding financial...

By Statistical Modeling, Causal Inference, and Social Science
An Application for Training Deep Learning Models in Your Browser
NewsApr 9, 2026

An Application for Training Deep Learning Models in Your Browser

Jordan Anaya has launched a web application, aleaaxis.net, that enables users to train deep learning models directly in their browsers. The tool is positioned as an educational platform to introduce students to AI without requiring local installations. Early user feedback...

By Statistical Modeling, Causal Inference, and Social Science
Updike in Tehran
NewsApr 8, 2026

Updike in Tehran

The author reflects on John Updike’s two‑volume collected stories, highlighting the early‑2000s tale “The Varieties of Religious Experience.” The story uniquely frames the 9/11 attacks from multiple viewpoints, including an elderly Updike‑type narrator, a hijacker, and a plane passenger. While...

By Statistical Modeling, Causal Inference, and Social Science
My (Uninformed and Completely Speculative) Theory About Jeff Bezos and the Washington Post
NewsApr 6, 2026

My (Uninformed and Completely Speculative) Theory About Jeff Bezos and the Washington Post

In 2013 Jeff Bezos purchased The Washington Post, a move that sparked debate about billionaire motives in a shrinking newspaper market. While the acquisition offered prestige, a potential political shield, and a possible digital‑media upside, the paper has become a...

By Statistical Modeling, Causal Inference, and Social Science
How Do Political Organizations and Politically-Minded Rich People Translate Money Into Media Influence?  Differently than They Used To.
NewsApr 5, 2026

How Do Political Organizations and Politically-Minded Rich People Translate Money Into Media Influence? Differently than They Used To.

The article traces the evolution of political money flowing into media, from early partisan newspapers to modern right‑wing ownership of TV networks, digital outlets, and social platforms. It notes that the removal of the Fairness Doctrine and rising polarization enabled...

By Statistical Modeling, Causal Inference, and Social Science
Black and White, Gray and in Between: What Color Is the Media?
NewsMar 31, 2026

Black and White, Gray and in Between: What Color Is the Media?

The article examines the limited media coverage of ETH Zurich professor Tom Crowther’s tenure denial after bullying and harassment complaints, highlighting his use of lab funds for crisis‑communication services. It draws parallels to the reopened Noma restaurant under chef René Redzepi, noting...

By Statistical Modeling, Causal Inference, and Social Science
Frank Harrell on Why and How to Do Bayes for Clinical Trials and the Recent FDA Draft Guidelines
NewsMar 26, 2026

Frank Harrell on Why and How to Do Bayes for Clinical Trials and the Recent FDA Draft Guidelines

Frank Harrell, a former FDA statistician, responded to recent JAMA commentary on the agency’s draft guidance promoting Bayesian methods for clinical trials. He highlighted that while the guidance is a step forward, FDA reviewers still rely on traditional frequentist approaches...

By Statistical Modeling, Causal Inference, and Social Science
Claimed “100% Sensitivity and Specificity in Differentiating Autistic Individuals From Typically Developing Controls Using Retinal Photographs” . . . Yeah,...
NewsMar 21, 2026

Claimed “100% Sensitivity and Specificity in Differentiating Autistic Individuals From Typically Developing Controls Using Retinal Photographs” . . . Yeah,...

Two recent JAMA Network Open studies report near‑perfect diagnostic performance for autism using retinal photographs and video‑based deep‑learning models. The retinal study claims 100 % sensitivity and specificity across 958 participants, while the video study reports an AUC above 0.99. Critics...

By Statistical Modeling, Causal Inference, and Social Science
Statistical Modeling, Causal Inference, and Social Science | Pulse