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politicalsciencenow.com /1 month ago

2026 Short Course Highlight: Causal Inference with Observational Data

Causal Inference with Observational Data Half Day Short Course | Register here 2026 APSA Annual Meeting & Exhibition — Boston, MA 9:00 am – 1:00 pm Estimating treatment effects...

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medium.com /1 week ago

Causal Inference in Finance: Moving Beyond “What Happened?” to “What Actually Worked?”

Why the patterns in your dashboards might be lying to youContinue reading on Medium »

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statmodeling.stat.columbia.edu /1 month ago

“The Data Analyst’s Guide to Cause and Effect”

Theiss Bendixen and Benjamin Grant Purzycki wrote this book. He writes: The website holds: – All data and code used in the book – Free sample chapters – Bonus material These aren’t...

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statmodeling.stat.columbia.edu /1 month ago

Epidemiologist Donna Spiegelman sez: SUTVA is “mostly not necessary for valid causal estimation and inference most of t...

Donna Spiegelman shares this presentation she gave at the recent American Causal Inference Conference. I like what she has to say. Here are the two parts of the stable treatment va...

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ajay-deshpande.medium.com /1 month ago

# Why Most Data Science Doesn’t Answer the Question You’re Asking

*This is the introduction to a series on causal inference — one of the most practically important and least taught topics in data science…Continue reading on Medium »

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towardsdatascience.com /1 month ago

LLM Themes Are Not Observations

A practitioner's warning about generated variables in causal analysis The post LLM Themes Are Not Observations appeared first on Towards Data Science.

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dev.to /1 month ago

I Built CausalLens — A Free, Open-Source Causal Impact Calculator for Time Series (5 Methods, Zero Setup)

I want to show you a tool I just open-sourced. It's called CausalLens, and it answers one specific question that most analytics stacks get completely wrong: did this intervention a...

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journals.plos.org /3 weeks ago

Variable selection-combined causal mediation analysis for continuous treatments with application to large-dimensional bi...

by Yajing Zhou, Kecheng Wei, Yahang Liu, Zhaoyang Li, Chen Huang, Guoyou Qin, Yongfu Yu Substantial progress has been made in the area of causal inference utilizing large-scale da...

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journals.plos.org /1 month ago

MR2G: A novel framework for causal network inference using GWAS summary data

by Zhaotong Lin, Wei Pan, Haoran Xue Inferring a causal network among multiple traits is essential for unraveling complex biological relationships and informing interventions. Men...

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journals.plos.org /17 hours ago

A generalized test of genotype–phenotype causality in population-sampled nuclear families

by Yushi Tang, John D. Storey We recently developed a causal inference framework and test—the Transmission Mean Test (TMT)—to identify causal genotype–phenotype relationships in p...

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statmodeling.stat.columbia.edu /1 month ago

What is the relation between interactions in a regression model and correlations among the predictors?

I’ve often seen confusion between interactions in a regression model and correlations among the predictors. To keep it simple, consider the model y = b0 + b1*x1 + b2*x2 + b3*x1*x2...

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towardsdatascience.com /2 days ago

Building Models in Two Worlds: From Latent Constructs to Behavioral Signals

My PhD models tried to explain why people engage. My industry models predict who will. The statistics barely changed. Everything around them did. The post Building Models in Two Wo...

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towardsdatascience.com /1 week ago

Granger Causal Networks and Indirect Feedback

A non-parametric variable selection for Structural VARs The post Granger Causal Networks and Indirect Feedback appeared first on Towards Data Science.

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politicalsciencenow.com /3 weeks ago

Short Course: Studying Causal Mechanisms Using In-Depth Case Studies (QMMR)

Studying Causal Mechanisms Using In-Depth Case Studies (QMMR) Half Day Short Course | Register here 2026 APSA Annual Meeting & Exhibition — Boston, MA 9:00 am – 1:00 pm The stu...

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medcitynews.com /2 weeks ago

Why Generative AI Isn’t Enough: The Case for Causal Reasoning in Medicine

AI built on transparent, causal reasoning, systems that ground every output in validated biological mechanisms, show the pathway behind each recommendation, and cite their sources...

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statmodeling.stat.columbia.edu /2 weeks ago

Survey Statistics: Big Changes in the Times/Siena Poll

Yesterday Nate Cohn wrote about The Big Changes Coming to the Times/Siena Poll, with more details in their poll of Maine. Say we want to estimate average Platner support in Maine’s...

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