3 papers
stat.ME2022
Robust analyses for longitudinal clinical trials with missing and non-normal continuous outcomes
Siyi Liu, Yilong Zhang, Gregory T Golm +3
Missing data is unavoidable in longitudinal clinical trials, and outcomes are not always normally distributed. In the presence of outliers or heavy-tailed distributions, the conven…
stat.ME2021
Multiply robust estimators in longitudinal studies with missing data under control-based imputation
Siyi Liu, Shu Yang, Yilong Zhang +2
Longitudinal studies are often subject to missing data. The ICH E9(R1) addendum addresses the importance of defining a treatment effect estimand with the consideration of intercurr…
stat.ME2020
SMIM: a unified framework of Survival sensitivity analysis using Multiple Imputation and Martingale
Shu Yang, Yilong Zhang, Guanghan Frank Liu +1
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 imputati…