TY - JOUR
T1 - Identification and inference for marginal average treatment effect on the treated with an instrumental variable
AU - Liu, Lan
AU - Miao, Wang
AU - Sun, Baoluo
AU - Robins, James
AU - Tchetgen, Eric Tchetgen
N1 - Publisher Copyright:
© 2020 Institute of Statistical Science. All rights reserved.
PY - 2020/7
Y1 - 2020/7
N2 - In observational studies, treatments are typically not randomized and, therefore, estimated treatment effects may be subject to a confounding bias. The instrumental variable (IV) design plays the role of a quasi-experimental handle because the IV is associated with the treatment and only affects the outcome through the treatment. In this paper, we present a novel framework for identification and inferences, using an IV for the marginal average treatment effect amongst the treated (ETT) in the presence of unmeasured confounding. For inferences, we propose three semiparametric approaches: (i) an inverse probability weighting (IPW); (ii) an outcome regression (OR); and (iii) a doubly robust (DR) estimation, which is consistent if either (i) or (ii) is consistent, but not necessarily both. A closed-form locally semiparametric efficient estimator is obtained in the simple case of a binary IV, and outcome, and the efficiency bound is derived for the more general case.
AB - In observational studies, treatments are typically not randomized and, therefore, estimated treatment effects may be subject to a confounding bias. The instrumental variable (IV) design plays the role of a quasi-experimental handle because the IV is associated with the treatment and only affects the outcome through the treatment. In this paper, we present a novel framework for identification and inferences, using an IV for the marginal average treatment effect amongst the treated (ETT) in the presence of unmeasured confounding. For inferences, we propose three semiparametric approaches: (i) an inverse probability weighting (IPW); (ii) an outcome regression (OR); and (iii) a doubly robust (DR) estimation, which is consistent if either (i) or (ii) is consistent, but not necessarily both. A closed-form locally semiparametric efficient estimator is obtained in the simple case of a binary IV, and outcome, and the efficiency bound is derived for the more general case.
KW - Counterfactuals
KW - Double robustness
KW - Effect of treatment on the treated
KW - Instrumental variable
KW - Unmeasured confounding
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U2 - 10.5705/ss.202017.0196
DO - 10.5705/ss.202017.0196
M3 - Article
C2 - 33209012
AN - SCOPUS:85091892509
SN - 1017-0405
VL - 30
SP - 1517
EP - 1541
JO - Statistica Sinica
JF - Statistica Sinica
IS - 3
ER -