Matching via Dimensionality Reduction for Estimation of Treatment Effects in Digital Marketing Campaigns

IJCAI, pp. 3768-3774, 2016.

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The matched counterparts of the treated units in the control group are interpreted as counterfactuals, and the average treatment effect on treated is estimated by comparing the outcomes of every matched pair

Abstract:

A widely used method for estimating counterfactuals and causal treatment effects from observational data is nearest-neighbor matching. This typically involves pairing each treated unit with its nearest-in-covariates control unit, and then estimating an average treatment effect from the set of matched pairs. Although straightforward to imp...More

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