Testing the effect of treatment on survival time with an immediate intermediate event

Johan Lim and Sungim Lee

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 8, 3718-3727

Abstract: In this paper, we consider testing the effects of treatment on survival time when a subject experiences an immediate intermediate event (IE) prior to death or predetermined endpoint. A two-stage model incorporating both (i) the effects of the covariates on the immediate IE and (ii) survival regression with the immediate IE and other covariates is presented. We study the likelihood ratio test (LRT) for testing the treatment effect based on the proposed two stage model. We propose two procedures: an asymptotic-based procedure and a resampling-based procedure, to approximate the null distribution of the LRT. We numerically show the advantages of the two stage modeling over the existing single stage survival model with interactions between the covariates and the immediate IE. In addition, an illustrative empirical example is provided.

Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2015.1071393 (text/html)
Access to full text is restricted to subscribers.

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:taf:lstaxx:v:46:y:2017:i:8:p:3718-3727

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2015.1071393

Access Statistics for this article

Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe

More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().