Investigating design for survival models

McGree, J. M. and Eccleston, J. A. (2010) Investigating design for survival models. Metrika, 72 3: 295-311. doi:10.1007/s00184-009-0254-3

Author McGree, J. M.
Eccleston, J. A.
Title Investigating design for survival models
Journal name Metrika   Check publisher's open access policy
ISSN 0026-1335
Publication date 2010
Year available 2009
Sub-type Article (original research)
DOI 10.1007/s00184-009-0254-3
Volume 72
Issue 3
Start page 295
End page 311
Total pages 17
Place of publication Heidelberg, Germany
Publisher Springer
Collection year 2011
Language eng
Subject C1
970101 Expanding Knowledge in the Mathematical Sciences
010405 Statistical Theory
Abstract The aim of this paper is to derive methodology for designing 'time to event' type experiments. In comparison to estimation, design aspects of 'time to event' experiments have received relatively little attention. We show that gains in efficiency of estimators of parameters and use of experimental material can be made using optimal design theory. The types of models considered include classical failure data and accelerated testing situations, and frailty models, each involving covariates which influence the outcome. The objective is to construct an optimal design based of the values of the covariates and associated model or indeed a candidate set of models. We consider D-optimality and create compound optimality criteria to derive optimal designs for multi-objective situations which, for example, focus on the number of failures as well as the estimation of parameters. The approach is motivated and demonstrated using common failure/survival models, for example, the Weibull distribution, product assessment and frailty models. © 2009 Springer-Verlag.
Keyword Accelerated life tests
Compound criteria
Compromise design
Frailty models
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ
Additional Notes Published online 25 March 2009.

Document type: Journal Article
Sub-type: Article (original research)
Collections: School of Mathematics and Physics
2010 Higher Education Research Data Collection
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Citation counts: TR Web of Science Citation Count  Cited 4 times in Thomson Reuters Web of Science Article | Citations
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Created: Tue, 20 Apr 2010, 17:08:09 EST by Kay Mackie on behalf of School of Mathematics & Physics