Regression analysis of longitudinal data with informative observation times and application to medical cost data
Article first published online: 22 FEB 2011
Copyright © 2011 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 30, Issue 12, pages 1429–1440, 30 May 2011
How to Cite
Zhu, L., Sun, J., Tong, X. and Pounds, S. (2011), Regression analysis of longitudinal data with informative observation times and application to medical cost data. Statist. Med., 30: 1429–1440. doi: 10.1002/sim.4198
- Issue published online: 10 MAY 2011
- Article first published online: 22 FEB 2011
- Manuscript Accepted: 17 DEC 2010
- Manuscript Received: 15 MAR 2010
- counting processes;
- latent variable model;
- longitudinal data analysis
Longitudinal data analysis is one of the most discussed and applied areas in statistics and a great deal of literature has been developed for it. However, most of the existing literature focus on the situation where observation times are fixed or can be treated as fixed constants. This paper considers the situation where these observation times may be random variables and more importantly, they may be related to the underlying longitudinal variable or process of interest. Furthermore, covariate effects may be time-varying. For the analysis, a joint modeling approach is proposed and in particular, for estimation of time-varying regression parameters, an estimating equation-based procedure is developed. Both asymptotic and finite sample properties of the proposed estimates are established. The methodology is applied to an acute myeloid leukemia trial that motivated this study. Copyright © 2011 John Wiley & Sons, Ltd.