Journal
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
Volume 79, Issue 4, Pages 1229-1245Publisher
OXFORD UNIV PRESS
DOI: 10.1111/rssb.12212
Keywords
Causal inference; Dose-response; Efficient influence function; Kernel smoothing; Semiparametric estimation
Categories
Funding
- National Institutes of Health [R01-DK090385]
- National Science Foundation [DMS-1352060, SES-1260782]
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Continuous treatments (e.g. doses) arise often in practice, but many available causal effect estimators are limited by either requiring parametric models for the effect curve, or by not allowing doubly robust covariate adjustment. We develop a novel kernel smoothing approach that requires only mild smoothness assumptions on the effect curve and still allows for misspecification of either the treatment density or outcome regression. We derive asymptotic properties and give a procedure for data-driven bandwidth selection. The methods are illustrated via simulation and in a study of the effect of nurse staffing on hospital readmissions penalties.
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