A causal proportional hazards estimator under homogeneous or heterogeneous selection in an IV setting

DOI10.1007/S10985-019-09476-YzbMath1436.62635OpenAlexW2943927485WikidataQ91841056 ScholiaQ91841056MaRDI QIDQ2305782

Ditte Nørbo Sørensen, Torben Martinussen, Eric J. Tchetgen Tchetgen

Publication date: 16 March 2020

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

Full work available at URL: https://doi.org/10.1007/s10985-019-09476-y

zbMATH Keywords

instrumental variablecausal effectselection bias functionstructural Cox modeltreatment effect on treated

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10) Estimation in survival analysis and censored data (62N02) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (1)

Instrumental Variable Estimation of the Causal Hazard Ratio

Uses Software

• timereg

Cites Work

• On instrumental variables estimation of causal odds ratios
• Introduction to empirical processes and semiparametric inference
• Dynamic regression models for survival data.
• Semiparametric theory and missing data.
• Attributable fraction functions for censored event times
• A Note on Formulae for Causal Mediation Analysis in an Odds Ratio Context
• A Causal Proportional Hazards Estimator for the Effect of Treatment Actually Received in a Randomized Trial with All-or-Nothing Compliance
• Estimation of treatment effects in randomised trials with non-compliance and a dichotomous outcome using structural mean models
• Identification of causal effects on binary outcomes using structural mean models
• Checking the Cox model with cumulative sums of martingale-based residuals
• Identification and Estimation of Local Average Treatment Effects
• Instrumental variables estimation of exposure effects on a time‐to‐event endpoint using structural cumulative survival models
• Causal Inference with Generalized Structural Mean Models
• Instrumental Variable Estimators for Binary Outcomes
• Estimating the Effect of Treatment in a Proportional Hazards Model in the Presence of Non-Compliance and Contamination
• Statistical models based on counting processes

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