Inverse Probability Weighted Estimation of Risk Under Representative Interventions in Observational Studies

DOI10.1080/01621459.2018.1469993zbMath1420.62152OpenAlexW2801522642WikidataQ90352916 ScholiaQ90352916MaRDI QIDQ5231520

Jessica G. Young, Miguel A. Hernán, Roger Logan, James M. Robins

Publication date: 27 August 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc6764781

zbMATH Keywords

longitudinal datasurvival analysiscausal inferencemarginal structural modelsg-formula

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Censored data models (62N01)

Related Items (2)

Nonparametric Tests of the Causal Null With Nondiscrete Exposures ⋮ Improved multiple quantile regression estimation with nonignorable dropouts

Cites Work

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• Population Intervention Causal Effects Based on Stochastic Interventions
• Identification, estimation and approximation of risk under interventions that depend on the natural value of treatment using observational data
• Unified methods for censored longitudinal data and causality
• Structural Nested Cumulative Failure Time Models to Estimate the Effects of Interventions
• A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect
• Inference for imputation estimators

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