Weighted estimating equations for longitudinal studies with death and non-monotone missing time-dependent covariates and outcomes
Article first published online: 20 JUN 2007
Copyright © 2007 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 27, Issue 7, pages 1008–1025, 30 March 2008
How to Cite
Shardell, M. and Miller, R. R. (2008), Weighted estimating equations for longitudinal studies with death and non-monotone missing time-dependent covariates and outcomes. Statist. Med., 27: 1008–1025. doi: 10.1002/sim.2964
- Issue published online: 7 FEB 2008
- Article first published online: 20 JUN 2007
- Manuscript Accepted: 7 MAY 2007
- Manuscript Received: 26 SEP 2006
- National Institute of Health. Grant Numbers: R37 AG09901, P60 AG12583
- weighted estimating equations;
- non-monotone missing data;
- longitudinal data
We propose a marginal modeling approach to estimate the association between a time-dependent covariate and an outcome in longitudinal studies where some study participants die during follow-up and both variables have non-monotone response patterns. The proposed method is an extension of weighted estimating equations that allows the outcome and covariate to have different missing-data patterns. We present methods for both random and non-random missing-data mechanisms. A study of functional recovery in a cohort of elderly female hip-fracture patients motivates the approach. Copyright © 2007 John Wiley & Sons, Ltd.