TY - JOUR
T1 - Instrumental variable estimation of weighted local average treatment effects
AU - Choi, Byeong Yeob
N1 - Funding Information:
This research was supported in part by the National Cancer Institute for the Mays Cancer Center (P30CA054174) at the UT Health Science Center at San Antonio.
Publisher Copyright:
© 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
PY - 2023
Y1 - 2023
N2 - Instrumental variable (IV) analysis addresses bias owing to unmeasured confounding when comparing two nonrandomized treatment groups. To date, studies in the statistical and biomedical literature have focused on the local average treatment effect (LATE), the average treatment effect for compliers. In this article, we study the weighted local average treatment effect (WLATE), which represents the weighted average treatment effect for compliers. In the WLATE, the population of interest is determined by either the instrumental propensity score or compliance score, or both. The LATE is a special case of the proposed WLATE, where the target population is the entire population of compliers. Here, we discuss the interpretation of a few special cases of the WLATE, identification results, inference methods, and optimal weights. We demonstrate the proposed methods with two published examples in which considerations of local causal estimands that deviate from the LATE are beneficial.
AB - Instrumental variable (IV) analysis addresses bias owing to unmeasured confounding when comparing two nonrandomized treatment groups. To date, studies in the statistical and biomedical literature have focused on the local average treatment effect (LATE), the average treatment effect for compliers. In this article, we study the weighted local average treatment effect (WLATE), which represents the weighted average treatment effect for compliers. In the WLATE, the population of interest is determined by either the instrumental propensity score or compliance score, or both. The LATE is a special case of the proposed WLATE, where the target population is the entire population of compliers. Here, we discuss the interpretation of a few special cases of the WLATE, identification results, inference methods, and optimal weights. We demonstrate the proposed methods with two published examples in which considerations of local causal estimands that deviate from the LATE are beneficial.
KW - Compliance scores
KW - Instrumental variables
KW - Local average treatment effects
KW - Weighted local average treatment effects
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U2 - 10.1007/s00362-023-01415-2
DO - 10.1007/s00362-023-01415-2
M3 - Article
AN - SCOPUS:85149213969
SN - 0932-5026
JO - Statistical Papers
JF - Statistical Papers
ER -