Sensitivity analysis for unmeasured confounding in a marginal structural Cox proportional hazards model

DOI10.1007/s10985-008-9109-xzbMath1282.62224OpenAlexW1983133304WikidataQ44903117 ScholiaQ44903117MaRDI QIDQ841066

Joe Sexton, Ole Klungsøyr, Jan F. Nygård, Inger Sandanger

Publication date: 14 September 2009

Published in: Lifetime Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10985-008-9109-x

zbMATH Keywords

sensitivity analysisselection biasunmeasured confounding

Mathematics Subject Classification ID

Reliability and life testing (62N05)

Related Items

Double Inverse-Weighted Estimation of Cumulative Treatment Effects Under Nonproportional Hazards and Dependent Censoring

Uses Software

• R

Cites Work

• Unnamed Item
• Addendum to ``A new approach to causal inference in mortality studies with a sustained exposure period. Application to control of the healthy worker survivor effect
• Bayesian inference for causal effects: The role of randomization
• Association, causation, and marginal structural models.
• Statistics and Causal Inference
• Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments
• Estimation of the Causal Effect of a Time-Varying Exposure on the Marginal Mean of a Repeated Binary Outcome
• Assessing the Sensitivity of Regression Results to Unmeasured Confounders in Observational Studies
• A new approach to causal inference in mortality studies with a sustained exposure period—application to control of the healthy worker survivor effect

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