Data Science, Statistics, Analytics, Experiment, Causality.
estimate the causal effect as: It’s called doubly robust because as long as at least one of the models (propensity or conditional mean) makes unbiased predictions, then this causal effect estimate is unbiased. In other words, even if we get one model wrong, we’re still fine. So why does this work