Partial Orders with Respect to Continuous Covariates and Tests for the Proportional Hazards Model

Arnab Bhattacharjee ()

Discussion Paper Series, Department of Economics from Department of Economics, University of St. Andrews

Abstract: Several omnibus tests of the proportional hazards assumption have been proposed in the literature. In the two-sample case, tests have also been developed against ordered alternatives like monotone hazard ratio and monotone ratio of cumulative hazards. Here we propose a natural extension of these partial orders to the case of continuous covariates. The work is motivated by applications in biomedicine and economics where covariate e¤ects often decay over lifetime. We develop tests for the proportional hazards assumption against ordered alternatives and propose a graphical method to identify the nature of departures from proportionality. The proposed tests do not make restrictive assumptions on the underlying regression model, and are applicable in the presence of multiple covariates and frailty. Small sample performance and applications to real data highlight the usefulness of the framework and methodology.

Keywords: Two-sample tests; Increasing hazard ratio; Continuous covariate; Proportional hazards; Frailty; Partial orders; Time varying coe¢cients. (search for similar items in EconPapers)
JEL-codes: C12 C14 C41 (search for similar items in EconPapers)
New Economics Papers: this item is included in nep-ecm
Date: 2008-07
View list of references View citations in EconPapers

Downloads: (external link)
http://www.st-andrews.ac.uk/academic/economics/papers/dp0807.pdf (application/pdf)

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: http://EconPapers.repec.org/RePEc:san:wpecon:0807

Ordering information: This working paper can be ordered from

Access Statistics for this paper

More papers in Discussion Paper Series, Department of Economics from Department of Economics, University of St. Andrews
Address: School of Economics and Finance, University of St. Andrews, Fife KY16 9AL
Series data maintained by Peter Macmillan ().