SMIM: A unified framework of survival sensitivity analysis using multiple imputation and martingale
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Publication:6056150
DOI10.1111/BIOM.13555zbMath1522.62271arXiv2007.02339OpenAlexW3193591524MaRDI QIDQ6056150
Shu Yang, Yilong Zhang, Qi'an Guan, Unnamed Author
Publication date: 30 October 2023
Published in: Biometrics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/2007.02339
delta adjustmentjump-to-referencerestrictive mean survival timerestrictive mean time losswild-bootstrap
Cites Work
- Unnamed Item
- Cox's regression model for counting processes: A large sample study
- Bootstrap procedures under some non-i.i.d. models
- Jackknife, bootstrap and other resampling methods in regression analysis
- Weighted resampling of martingale difference arrays with applications
- Semiparametric theory and missing data.
- A note on multiple imputation for method of moments estimation
- Methods for Conducting Sensitivity Analysis of Trials with Potentially Nonignorable Competing Causes of Censoring
- Causal Inference on the Difference of the Restricted Mean Lifetime Between Two Groups
- Inference and missing data
- Large-sample theory for parametric multiple imputation procedures
- Proportional hazards tests and diagnostics based on weighted residuals
- Estimation of the failure time distribution in the presence of informative censoring
- Pattern-Mixture Models for Multivariate Incomplete Data
- Inference for imputation estimators
- A Simple Method for Estimating Interactions Between a Treatment and a Large Number of Covariates
- Analysis of Failure Time Data Under Competing Censoring Mechanisms
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