Article first published online: 9 OCT 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 32, Issue 12, pages 2013–2030, 30 May 2013
How to Cite
Song, X. and Wang, C.-Y. (2013), Time-varying coefficient proportional hazards model with missing covariates. Statist. Med., 32: 2013–2030. doi: 10.1002/sim.5652
- Issue published online: 7 MAY 2013
- Article first published online: 9 OCT 2012
- Manuscript Accepted: 19 SEP 2012
- Manuscript Received: 18 APR 2012
- NIH. Grant Numbers: R01ES017030, CA53996
- NSF. Grant Number: DMS-1106816
- inverse probability weighting;
- local partial likelihood;
Missing covariates often arise in biomedical studies with survival outcomes. Existing approaches for missing covariates generally assume proportional hazards. The proportionality assumption may not hold in practice, as illustrated by data from a mouse leukemia study with covariate effects changing over time. To tackle this restriction, we study the missing data problem under the varying-coefficient proportional hazards model. On the basis of the local partial likelihood approach, we develop inverse selection probability weighted estimators. We consider reweighting and augmentation techniques for possible improvement of efficiency and robustness. The proposed estimators are assessed via simulation studies and illustrated by application to the mouse leukemia data. Copyright © 2012 John Wiley & Sons, Ltd.