Part II describes what you are asking for. I wish abbreviations like inverse probability weighting and marginal structural models were expanded in the second b

Part II describes what you are asking for. I wish abbreviations like inverse probability weighting and marginal structural models were expanded in the second book. It's annoying to have to look up "IP weighting" only to discover "oh, it's IPW, god damn you [authors] to hell". MSMs are interesting. Now I remember why Robins' name stuck in my head. The book shows all the math explicitly, which is nice, and it delves into causal inference for time-to-event data, which is also nice. Now I'm curious whether they look at piecewise constant survival models for time-varying coefficients. It's mentioned, but I didn't read enough to see if it's treated in detail. If it is, everyone who does A/B testing should read the book, because this is one of those "little details" from biostatistics that becomes super important at big retailers (like, say, Amazon, where the principal economist at the time pointed it out to me).