Other Standard Research Designs (The Effect, Videos on Causality, Ep 65)

Please visit www.theeffectbook.net to read The Effect online for free, or find links to purchase a physical copy or ebook.
The Effect is a book about research design and causal inference. How can we use data to learn about the world? How can we answer questions about whether X causes Y even if we can't run a randomized experiment? The book covers these things and plenty more. These videos are meant to accompany the book, although they can also be viewed on their own.
This video relates to material found in Chapter 21 of the book.
A version of this video without background music can be found here: • Other Standard Researc...
Who says we need to stop there? We've covered a number of "standard" template designs like difference-in-differences and regression discontinuity. But there are others! We won't have time to go into them in detail, but here's a quick rundown of some other causal inference designs that are widely applicable but you might not have heard of before.

[@TateVanPatten]

I just found your free online book! What a great resource! I took econometrics last year and am brushing up for a competition!

[@Tee_Cee_]

Thank you aGAIN! Just a token of support for your excellent content!

[@Tee_Cee_]

1) GREAT Vids!!! 2) Is a matrix completion my sole causal option if my IT/treatment has a dichotomous pattern that looks like 0;1;0;1;1;0;1;1;1;0 (suggesting compounding impacts) over a 10-yr period? I thought I'd be doing a DID until seeing my effect wasn't a one-n-done like a policy might be. Instead, I have staggered effects bc another site might have the first effect in year 7, then nothing again until year 10, PLUS what looks like a compounding effect on about 1500 sites annually over a decade. 3) Any suggestions?

[@NickHuntingtonKlein]

There are a few other approaches that allow for "non-monotonic treatment", Ie treatment that turns off and on. I haven't tried them myself so I can't vouch for any one in particular though. But that's the search term I'd use.

[@Tee_Cee_]

@@NickHuntingtonKlein TY, I'll do that! TBH, I've looked at using a DID with decomposition to show the weight differences in just-effected vs already effected groups vs their untreated counterparts, but IDK. This is all so complicated TBH. I'm now wondering if a fixed effects analysis is my safe route bc it feels like I'm diving repeatedly into the "How the Pros Do It" portion of your chapters! 😙Any thoughts?

[@NickHuntingtonKlein]

@@Tee_Cee_ Fixed effects won't make use of the "control group" element of the design. Using something that takes that into account will probably give you a more plausible estimate. Something to note is that what you want to do here needs to keep in mind what you think the fadeout of the effect is. If you expect the treatment to have a lasting effect of any kind, then in a treatment pattern of 1, 0, 1, etc., the unit is still being treated to some degree in the 0 period. THinking about this again you may instead want to look at this paper www.nber.org/system/files/working_papers/w29873/w29873.pdf and the associated software packages did_multiplegt (stata) and DIDmultiplegt (R)

[@Tee_Cee_]

@@NickHuntingtonKlein Considering all of this, and reading! TY for the guidance!