Estimating the causal effects in randomized trials for survival data with a cure fraction and non compliance

DOI10.1080/03610926.2015.1076481zbMath1368.62277OpenAlexW2563007685MaRDI QIDQ4976276

Xiang Gao, Ming Zheng

Publication date: 27 July 2017

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2015.1076481

zbMATH Keywords

EM algorithmtransformation modelcure modelnonparametric likelihoodall-or-none compliance

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02)

Cites Work

• Correcting for non-compliance in randomized trials using rank preserving structural failure time models
• Bayesian inference for causal effects: The role of randomization
• On the application of probability theory to agricultural experiments. Essay on principles. Section 9. Translated from the Polish and edited by D. M. Dąbrowska and T. P. Speed
• Semiparametric Estimation and Inference for Distributional and General Treatment Effects
• A Causal Proportional Hazards Estimator for the Effect of Treatment Actually Received in a Randomized Trial with All-or-Nothing Compliance
• On semiparametric transformation cure models
• Efficient estimation of semiparametric transformation models for counting processes
• Efficient nonparametric estimation of causal effects in randomized trials with noncompliance
• Identification and Estimation of Local Average Treatment Effects
• Estimating Outcome Distributions for Compliers in Instrumental Variables Models
• A Proportional Hazards Model Taking Account of Long-Term Survivors
• Semiparametric Transformation Models for Survival Data With a Cure Fraction
• Bayesian survival analysis

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