Latest updates for Causalml

Fresh curated links around causalml are collected here so marketers can spot useful updates and turn timely ideas into posts faster.

Recent items include:

  • LLM Themes Are Not Observations
  • Causal Inference in Finance: Moving Beyond “What Happened?” to “What Actually Worked?”
  • “The Data Analyst’s Guide to Cause and Effect”

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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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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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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 /23 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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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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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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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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Sources covering Causalml

dev.to

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journals.plos.org

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journals.plos.org

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medium.com

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statmodeling.stat.columbia.edu

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towardsdatascience.com

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