Regression analysis of multivariate recurrent event data with time-varying covariate effects
Recurrent event data occur in many fields and many approaches have been proposed for their analyses (Andersen et al. (1993)Â [1]; Cook and Lawless (2007)Â [3]). However, most of the available methods allow only time-independent covariate effects, and sometimes this may not be true. In this paper, we consider regression analysis of multivariate recurrent event data in which some covariate effects may be time-dependent. For the problem, we employ the marginal modeling approach and, especially, estimating equation-based inference procedures are developed. Both asymptotic and finite-sample properties of the proposed estimates are established and an illustrative example is provided.
Year of publication: |
2009
|
---|---|
Authors: | Sun, Liuquan ; Zhu, Liang ; Sun, Jianguo |
Published in: |
Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 100.2009, 10, p. 2214-2223
|
Publisher: |
Elsevier |
Keywords: | Event history study Marginal models Recurrent event data Time-varying coefficients |
Saved in:
Saved in favorites
Similar items by person
-
Semiparametric regression analysis of longitudinal data with informative observation times
Sun, Jianguo, (2005)
-
Sun, Jianguo, (2007)
-
Regression Analysis of Doubly Censored Failure Time Data Using the Additive Hazards Model
Sun, Liuquan, (2004)
- More ...