Multiple imputation based on restricted mean model for censored data
Article first published online: 11 JAN 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 30, Issue 12, pages 1339–1350, 30 May 2011
How to Cite
Liu, L. X., Murray, S. and Tsodikov, A. (2011), Multiple imputation based on restricted mean model for censored data. Statist. Med., 30: 1339–1350. doi: 10.1002/sim.4163
- Issue published online: 10 MAY 2011
- Article first published online: 11 JAN 2011
- Manuscript Accepted: 28 OCT 2010
- Manuscript Received: 22 JAN 2010
- multiple imputation;
- restricted mean lifetime;
Most multiple imputation (MI) methods for censored survival data either ignore patient characteristics when imputing a likely event time, or place quite restrictive modeling assumptions on the survival distributions used for imputation. In this research, we propose a robust MI approach that directly imputes restricted lifetimes over the study period based on a model of the mean restricted life as a linear function of covariates. This method has the advantages of retaining patient characteristics when making imputation choices through the restricted mean parameters and does not make assumptions on the shapes of hazards or survival functions. Simulation results show that our method outperforms its closest competitor for modeling restricted mean lifetimes in terms of bias and efficiency in both independent censoring and dependent censoring scenarios. Survival estimates of restricted lifetime model parameters and marginal survival estimates regain much of the precision lost due to censoring. The proposed method is also much less subject to dependent censoring bias captured by covariates in the restricted mean model. This particular feature is observed in a full statistical analysis conducted in the context of the International Breast Cancer Study Group Ludwig Trial V using the proposed methodology. Copyright © 2011 John Wiley & Sons, Ltd.