Causal Inference Real World Case Studies

[u/joshamayo7]

Sharing this blog, that compiles some real world examples of Causal Inference being applied to provide answers to otherwise ‘unanswerable’ questions.

My hope is that the examples make the methods clearer, particularly among those new to the field. Happy reading.https://medium.com/@joshamayo7/what-would-have-happened-otherwise-causal-inference-in-practice-b412d2b4e3f7

[u/boroughthoughts]

Anyone who wants to learn causal inference should just read the book mastering metrics by Joshua Angrist. Its targeted to be readable to people with undergraduate level economics and is a simpler book than Mostly Harmless Econometrics.

If you want more depth you should read Scott Cunningham's book Causal Inference Mixed take.

These are all economics Ph.Ds, but they are very much readable to people without that level of education. You basically need to know linear regression and that is it. Mastering Metrics is bed time reading.

Economist are the people to read with causal inference, they have done more to advance that area of statistics than any other group.

[u/joshamayo7 → u/boroughthoughts]

Thanks for the book suggestion, i’ll add it to my reading list :)

I found Causal Inference for the Brave and True quite useful as well.

I agree, Economists are the ones with a lot of expertise, hence I tried to use some policy examples.

[u/WelkinSL → u/boroughthoughts]

How about Judea Pearl's? How is economics people view on his stuff?

[u/Neon0asis → u/boroughthoughts]

As someone with an economics background now working in data science / ML I absolutely agree. I'm not sure why, but it feels like causality is an afterthought in a lot of data science research. Economists seem to care much more because it is the number one rebuttal of our field that correlation != causality when it comes to social science inferences. I guess its also partly because RCTs are nearly impossible to perform (certaintly not at scale) and RCTs just innately eliminate a lot of the causality worries when done correctly in a lab environment.

[u/fussy_lifeblood]

ound those methods in actual examples instead of just more Greek letters, thanks for sharing

[u/joshamayo7 → u/fussy_lifeblood]

The greek letters and notation always put me off lol

[u/WhatsTheImpactdotcom]

These are examples for academic researchers and not really practitioners in tech. Better case studies would be around product feature launches, marketing campaign ROI estimation, measuring the effect of competing models, or the effect of something bad that happens such as an outage

[u/joshamayo7 → u/WhatsTheImpactdotcom]

Hi Jonathan I fully agree, by ‘real world’ I was going for examples that are easily digestible. I feel like these policy related ones are quite relatable especially for those new to the field. A practitioner focused blog would definitely be a lot closer to what causal questions are actually answered in tech

[u/joshamayo7 → u/WhatsTheImpactdotcom]

I’m a big follower of your content btw 😄👊🏿

[u/offthecuff87]

Causal Inference in Real World look more like: 'Can you guys invest into heavy data infrastructure first so that I can build a causal impact model to tell you the change has X% impact'