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Instrumental variable method for time‐to‐event data using a pseudo‐observation approach
Author(s) -
Kjaersgaard Maiken I. S.,
Parner Erik T.
Publication year - 2016
Publication title -
biometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.298
H-Index - 130
eISSN - 1541-0420
pISSN - 0006-341X
DOI - 10.1111/biom.12451
Subject(s) - instrumental variable , confounding , observational study , statistics , econometrics , variable (mathematics) , computer science , event (particle physics) , estimation , mathematics , economics , mathematical analysis , physics , management , quantum mechanics
Summary Observational studies are often in peril of unmeasured confounding. Instrumental variable analysis is a method for controlling for unmeasured confounding. As yet, theory on instrumental variable analysis of censored time‐to‐event data is scarce. We propose a pseudo‐observation approach to instrumental variable analysis of the survival function, the restricted mean, and the cumulative incidence function in competing risks with right‐censored data using generalized method of moments estimation. For the purpose of illustrating our proposed method, we study antidepressant exposure in pregnancy and risk of autism spectrum disorder in offspring, and the performance of the method is assessed through simulation studies.