The University of Southampton
University of Southampton Institutional Repository

Optimal designs for full and partial likelihood information - with application to survival models

Optimal designs for full and partial likelihood information - with application to survival models
Optimal designs for full and partial likelihood information - with application to survival models
Time-to-event data are often modelled through Cox's proportional hazards model for which inference is based on the partial likelihood function. We derive a general expression for the asymptotic covariance matrix of Cox's partial likelihood estimator for the covariate coefficients. Our approach is illustrated through an application to the special case of only one covariate, for which we construct minimum variance designs for different censoring mechanisms and both binary and interval design spaces. We compare these designs with the corresponding ones found using the full likelihood approach and demonstrate that the latter designs are highly efficient also for partial likelihood estimation.
right-censoring, cox's proportional hazards model, optimal design, full likelihood, partial likelihood
0378-3758
27–37
Konstantinou, Maria
242713ea-332c-466d-82e5-b2d6aa8dad07
Biedermann, S.
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Kimber, Alan C.
40ba3a19-bbe3-47b6-9a8d-68ebf4cea774
Konstantinou, Maria
242713ea-332c-466d-82e5-b2d6aa8dad07
Biedermann, S.
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Kimber, Alan C.
40ba3a19-bbe3-47b6-9a8d-68ebf4cea774

Konstantinou, Maria, Biedermann, S. and Kimber, Alan C. (2015) Optimal designs for full and partial likelihood information - with application to survival models. Journal of Statistical Planning and Inference, 165, 27–37. (doi:10.1016/j.jspi.2015.03.007).

Record type: Article

Abstract

Time-to-event data are often modelled through Cox's proportional hazards model for which inference is based on the partial likelihood function. We derive a general expression for the asymptotic covariance matrix of Cox's partial likelihood estimator for the covariate coefficients. Our approach is illustrated through an application to the special case of only one covariate, for which we construct minimum variance designs for different censoring mechanisms and both binary and interval design spaces. We compare these designs with the corresponding ones found using the full likelihood approach and demonstrate that the latter designs are highly efficient also for partial likelihood estimation.

Text
coxmodel for eprints.pdf - Accepted Manuscript
Download (312kB)

More information

Accepted/In Press date: 14 March 2015
e-pub ahead of print date: 2 April 2015
Published date: 1 October 2015
Additional Information: Published in the October 2015 volume
Keywords: right-censoring, cox's proportional hazards model, optimal design, full likelihood, partial likelihood
Organisations: Statistical Sciences Research Institute

Identifiers

Local EPrints ID: 366672
URI: http://eprints.soton.ac.uk/id/eprint/366672
ISSN: 0378-3758
PURE UUID: 834e67f1-cd3f-4d51-a951-31cae7f314e6
ORCID for S. Biedermann: ORCID iD orcid.org/0000-0001-8900-8268

Catalogue record

Date deposited: 04 Jul 2014 15:47
Last modified: 18 Feb 2021 17:07

Export record

Altmetrics

Contributors

Author: Maria Konstantinou
Author: S. Biedermann ORCID iD
Author: Alan C. Kimber

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×