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Comment on Causal inference as a blind spot of data scientistsparent

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just use propensity scores + ipw and you have the same thing as a rct. :)

From my experience propensity scores + ipw really doesn't get you far in practice. Propensity scoring models rarely balance all the covariates well (more often, one or two are marginally better and some may be worse than before). On top of that, IPW either assumes you don't have any cases of extreme imbalance, or, if you do you end up trimming weights to avoid adding additional variance, but in some cases you do even with trimmed weights..

not necessarily unless you skim over meaningful confounding factors :)

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