Sensitivity analysis for informative censoring in parametric survival models: an evaluation of the method
Sensitivity analysis for informative censoring in parametric survival models: an evaluation of the method
In a paper by Siannis, Copas and Lu in Biostatistics, the authors proposed and studied a sensitivity analysis for informative censoring in parametric survival analysis. More specifically, they introduced a parametric model that allows for dependence between the failure and censoring processes in terms of a parameter delta which can be thought of as measuring the size of the dependence between the two processes, and a bias function that measures the pattern of this dependence. Based on this model, for small values of delta, they also derived simplified closed form expressions (approximations) for the sensitivity analysis of the associated parameters of the model. Since then, some extensions of this approach have also appeared in the literature. In this paper, some theoretical issues concerning the above approach are discussed. Then the results of an extensive simulation study are reported, which indicate some shortcomings of the proposed sensitivity analysis, particularly in the presence of nuisance parameters.
University of Southampton
Bompotas, Panagiotis
0194cce6-3619-4378-96eb-a7a14e849607
Kimber, Alan
40ba3a19-bbe3-47b6-9a8d-68ebf4cea774
Biedermann, Stefanie
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Bompotas, Panagiotis
0194cce6-3619-4378-96eb-a7a14e849607
Kimber, Alan
40ba3a19-bbe3-47b6-9a8d-68ebf4cea774
Biedermann, Stefanie
fe3027d2-13c3-4d9a-bfef-bcc7c6415039
Bompotas, Panagiotis, Kimber, Alan and Biedermann, Stefanie
(2017)
Sensitivity analysis for informative censoring in parametric survival models: an evaluation of the method
Southampton.
University of Southampton
15pp.
(Submitted)
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Monograph
(Project Report)
Abstract
In a paper by Siannis, Copas and Lu in Biostatistics, the authors proposed and studied a sensitivity analysis for informative censoring in parametric survival analysis. More specifically, they introduced a parametric model that allows for dependence between the failure and censoring processes in terms of a parameter delta which can be thought of as measuring the size of the dependence between the two processes, and a bias function that measures the pattern of this dependence. Based on this model, for small values of delta, they also derived simplified closed form expressions (approximations) for the sensitivity analysis of the associated parameters of the model. Since then, some extensions of this approach have also appeared in the literature. In this paper, some theoretical issues concerning the above approach are discussed. Then the results of an extensive simulation study are reported, which indicate some shortcomings of the proposed sensitivity analysis, particularly in the presence of nuisance parameters.
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Submitted date: 2017
Organisations:
Statistics, Statistical Sciences Research Institute
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Local EPrints ID: 405655
URI: http://eprints.soton.ac.uk/id/eprint/405655
PURE UUID: 6220e42f-d15d-45ab-8e19-1168a260eeb8
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Date deposited: 10 Feb 2017 10:37
Last modified: 16 Mar 2024 03:51
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Author:
Panagiotis Bompotas
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