Estimating treatment effect in a proportional hazards model in randomized clinical trials with all-or-nothing compliance

DOI10.1111/BIOM.12472zbMath1390.62284OpenAlexW2292003484WikidataQ37420469 ScholiaQ37420469MaRDI QIDQ2827183

Shuli Li, Robert J. Gray

Publication date: 12 October 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc5113714

zbMATH Keywords

EM algorithmproportional hazards modelrandomized clinical trialweighted partial likelihoodall-or-nothing compliance

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (4)

Instrumental variable estimation of complier causal treatment effect with interval‐censored data ⋮ Estimation of complier causal treatment effects with informatively interval-censored failure time data ⋮ Estimation of complier causal treatment effects under the case–cohort studies with interval-censored failure time data ⋮ Unnamed Item

Cites Work

• Unnamed Item
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• Semiparametric instrumental variable estimation of treatment response models.
• Principal Stratification in Causal Inference
• A Causal Proportional Hazards Estimator for the Effect of Treatment Actually Received in a Randomized Trial with All-or-Nothing Compliance
• Identification of Causal Effects Using Instrumental Variables
• Estimation of treatment effects in randomised trials with non-compliance and a dichotomous outcome using structural mean models
• Marginal Structural Models to Estimate the Joint Causal Effect of Nonrandomized Treatments
• Proportional Hazards Regression with Missing Covariates
• On Profile Likelihood

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