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AUGMENTED MINIMAX LINEAR ESTIMATION
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DOI：10.1214/21-AOS2080.png)
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摘要
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Many statistical estimands can expressed as continuous linear functionals of a conditional expectation function. This includes the average treatment effect under unconfoundedness and generalizations for continuous-valued and personalized treatments. In this paper, we discuss a general approach to estimating such quantities: we begin with a simple plug-in estimator based on an estimate of the conditional expectation function, and then correct the plugin estimator by subtracting a minimax linear estimate of its error. We show that our method is semiparametrically efficient under weak conditions and observe promising performance on both real and simulated data.
Keyword:
Causal inference
convex optimization
semiparametric efficiency
期刊
IF:
3.7
论文数:
2.8K
被引数:
2.9W
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