Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/14965
Title: Optimal designs for full and partial likelihood information - With application to survival models
Authors: Konstantinou, Maria 
Biedermann, Stefanie 
Kimber, Alan C. 
Major Field of Science: Agricultural Sciences
Field Category: Environmental Biotechnology;Other Agricultural Sciences
Keywords: Cox's model;Full likelihood;Optimal design;Partial likelihood;Right-censoring
Issue Date: 1-Oct-2015
Source: Journal of Statistical Planning and Inference, 2015, vol, 165, pp. 27-37.
Volume: 165
Start page: 27
End page: 37
Journal: Journal of Statistical Planning and Inference 
Abstract: © 2015 Elsevier B.V. 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.
ISSN: 0378-3758
DOI: 10.1016/j.jspi.2015.03.007
Rights: © Elsevier
Attribution-NonCommercial-NoDerivs 3.0 United States
Type: Article
Affiliation : University of Southampton 
Ruhr-Universität Bochum 
Appears in Collections:Άρθρα/Articles

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