SMIM: A unified framework of Survival sensitivity analysis using Multiple Imputation and Martingale.

@article{Yang2021SMIMAU,
  title={SMIM: A unified framework of Survival sensitivity analysis using Multiple Imputation and Martingale.},
  author={Shu Yang and Yilong Zhang and Guanghan Frank Liu and Qian Guan},
  journal={Biometrics},
  year={2021}
}
Censored survival data are common in clinical trial studies. We propose a unified framework for sensitivity analysis to censoring at random in survival data using multiple imputation and martingale, called SMIM. The proposed framework adopts the δ-adjusted and control-based models, indexed by the sensitivity parameter, entailing censoring at random and a wide collection of censoring not at random assumptions. Also, it targets a broad class of treatment effect estimands defined as functionals of… 

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