### Summary of topic Causal inference papers and notes. ### Papers - [[Paper_Gelman_2011_CausalityAndStatisticalLearning]] #### Resources - [[Fisher's Sharp Null]] - [[Threats to validity of randomized experiments]] - [[Book_Cunningham_2021_CausalInferenceMixtape | Causal Inference: The Mixtape (Book)]] - [[Damon Centola]] - [[Gary King]] - [Ben Lambert (YouTube)](https://www.youtube.com/user/SpartacanUsuals): some introductory econometrics lectures on key topics. - [Kosuke Imai's](https://imai.fas.harvard.edu/index.html) [*Causal Inference with Applications* Course](https://imai.fas.harvard.edu/teaching/cause.html): slides and lecture videos on YouTube - [[Matching for Causal Inference]] - [[Network Experimentation]] - [This causal inference course syllabus](https://jonnyphillips.github.io/FLS6415/Syllabus.pdf) for more reading. - This [online jupyter book](https://matheusfacure.github.io/python-causality-handbook/landing-page.html) - [Mostly Harmless Econometrics Webcasts](https://www.aeaweb.org/conference/cont-ed/2020-webcasts) - [Mostly Harmless Econometrics online PDF](https://jonnyphillips.github.io/FLS6415/Class_3/Angrist%20&%20Pischke.pdf) - There is also [this repo](https://github.com/vikjam/mostly-harmless-replication) which implements exercises in the textbook in multiple programming languages, including [[00 - Python Map | Python]]. - [The Effect: An Introduction to Research Design and Causality](https://www.theeffectbook.net/) (free online book) - [Video playlist for this book](https://www.youtube.com/playlist?list=PLcTBLulJV_AK1hKtnO0-kYrU0D09K-kj8) - [Causality: Models, Reasoning and Inference](https://www.amazon.com/Causality-Reasoning-Inference-Judea-Pearl/dp/052189560X/ref=asc_df_052189560X/?tag=hyprod-20&linkCode=df0&hvadid=312091458201&hvpos=&hvnetw=g&hvrand=2312402412662744559&hvpone=&hvptwo=&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=9016568&hvtargid=pla-460203301899&psc=1&tag=&ref=&adgrpid=63669393113&hvpone=&hvptwo=&hvadid=312091458201&hvpos=&hvnetw=g&hvrand=2312402412662744559&hvqmt=&hvdev=c&hvdvcmdl=&hvlocint=&hvlocphy=9016568&hvtargid=pla-460203301899) (Judea Pearl's textbook): The first couple of chapters were highly recommended by YY - [PyWhy](https://github.com/py-why) - [DoWhy](https://github.com/py-why/dowhy) --- #### Related #causal_inference