Causal design patterns for data analysts | Emily Riederer

[utterances-bot]

Causal design patterns for data analysts | Emily Riederer

An informal primer to causal analysis designs and data structures

https://emilyriederer.netlify.app/post/causal-design-patterns/

[Saguedo97]

Really interesting post, thanks for sharing and for the resources!

[aquacalc]

Very informative, well organized, and particularly well written. Thanks.

[tbata]

Lovely post ! ...so well written and insightful. I would love to use some of your Mnemonic illustrations for my own teaching material (M. Sc course Data science in Bioinformaticsand B. Sc course An introduction to data science in R, both at AArhus University, Denmark). Thanks Thomas.

[emilyriederer]

Thanks for letting me know, @tbata ! Please help yourself! If you're interested, this deck version has a few more illustrations that didn't make the cut for the original blog. Specifically, slides 13-17 illustrate the mathematics behind deriving propensity score weights, and slide 26 briefly scratches the surface on some of the modern diff-in-diff alternatives.

[tbata]

Thanks for your quick answer and for sharing your slides These are neat illustrations ! By the way I just came across your talk at the u of Toronto reproducibility on line workshop.. also v interesting. All the best Thomas On 28 Mar 2021, at 13.22, Emily Riederer ***@***.***> wrote:  Thanks for letting me know, @tbata<https://github.com/tbata> ! Please help yourself! If you're interested, this deck version<https://docs.google.com/presentation/d/1_gItoNO4lfrgrPfRCSlq833hIrw1iNZ2RcltCCkPspc/edit?usp=sharing> has a few more illustrations that didn't make the cut for the original blog. Specifically, slides 13-17 illustrate the mathematics behind deriving propensity score weights, and slide 26 briefly scratches the surface on some of the modern diff-in-diff alternatives. — You are receiving this because you were mentioned. Reply to this email directly, view it on GitHub<#21 (comment)>, or unsubscribe<https://github.com/notifications/unsubscribe-auth/ACXXFTQ2TA4RZQDIHA3JW4TTF4GO7ANCNFSM4X5PEM5A>.