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Our revised #CausalInferenceBook is now freely available.
The book is organized in 3 parts of increasing difficulty: From counterfactuals and causal diagrams to treatment-confounder feedback and g-methods.
Thanks to everyone who sent us comments/typos.
hsph.harvard.edu/miguel-hernan/…
The book is organized in 3 parts of increasing difficulty: From counterfactuals and causal diagrams to treatment-confounder feedback and g-methods.
Thanks to everyone who sent us comments/typos.
hsph.harvard.edu/miguel-hernan/…
Free code for the #CausalInferenceBook in R, SAS, Stata, and Python.
Now updated and available through the book's web page.
hsph.harvard.edu/miguel-hernan/…
We are indebted to Roger Logan, @EpiEllie, Joy Shi, Sean McGrath, and James Fiedler. Thanks!
#Rstats @Stata @SASsoftware @ThePSF
Now updated and available through the book's web page.
hsph.harvard.edu/miguel-hernan/…
We are indebted to Roger Logan, @EpiEllie, Joy Shi, Sean McGrath, and James Fiedler. Thanks!
#Rstats @Stata @SASsoftware @ThePSF
Of all the things that excellent data scientists can do in their free time, I am so happy that Sam Finlayson (@IAmSamFin) chose this.
Thanks for helping us make the #CausalInferenceBook more accessible, Sam. I owe you one.
Thanks for helping us make the #CausalInferenceBook more accessible, Sam. I owe you one.
1/n I agree with @yudapearl of the utterly brilliant contribution of Sewall Wright, who pioneered both ways of representing data and developing the "background knowledge" of how genetics provides the necessary causal anchoring for meaningful inference bristol.ac.uk/media-library/…
2/n it is comic of @yudapearl to suggest #bookofwhy sees year zero of the causal revolution as Wright -attached from preface, Causal Revolution was in the womb of artificial intelligence (term introduced 1956, but what is meant is @yudapearl work in AI) … 
3/n Some of that "background knowledge" in real-world causal inference is that something can't be in the womb 70 years after it’s born. Absorb the tone of the rest of the preface, or read @yudapearl twitter feed, or the book. How do other #causalinferencebook readers see this?
