Sufficient dimension reduction on marginal regression for gaps of recurrent events

Xiaobing Zhao and Xian Zhou

Journal of Multivariate Analysis, 2014, vol. 127, issue C, 56-71

Abstract: A semiparametric linear transformation of gap time is proposed to model recurrent event data with high-dimensional covariates and informative censoring. It is derived from a proportional hazards model for the conditional intensity function of a renewal process. To overcome the difficulty arising from high-dimensional covariates, we develop a modified sliced regression for censored data and use a sufficient dimension reduction procedure to transform them to a lower dimensional space. Simulation studies are performed to confirm and evaluate the theoretical findings, and to compare the proposed method with existing methods in the literature. An example of application on a set of medical data is demonstrated as well. The proposed model together with the dimension reduction method offers an effective alternative for the analysis of recurrent event with high-dimensional covariates and informative censoring.

Keywords: Semiparametric transformation; Gap time; Recurrent event; High-dimensional covariates; Sliced regression; Sufficient dimension reduction (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X14000165
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:127:y:2014:i:c:p:56-71

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.jmva.2014.01.008

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().