Application of the Vertex Exchange Method to estimate a semi-parametric mixture model for the MIC density of Escherichia coli isolates tested for susceptibility against ampicillin
Application of the Vertex Exchange Method to estimate a semi-parametric mixture model for the MIC density of Escherichia coli isolates tested for susceptibility against ampicillin
In the last decades, considerable attention has been paid to the collection of antimicrobial resistance data, with the aim of monitoring non-wild-type isolates. This monitoring is performed based on minimum inhibition concentration (MIC) values, which are collected through dilution experiments. We present a semi-parametric mixture model to estimate the entire MIC density on the continuous scale. The parametric first component is extended with a non-parametric second component and a new back-fitting algorithm, based on the Vertex Exchange Method, is proposed. Our data example shows how to estimate the MIC density for Escherichia coli tested for ampicillin and how to use this estimate for model-based classification. A simulation study was performed, showing the promising behavior of the new method, both in terms of density estimation as well as classification.
94-107
Jaspers, Stijn
25595386-1f13-494a-82a6-f48dfff0e9a0
Verbeke, Geert
6ff74f99-0e82-4183-a97d-8bbf0b6708bb
Bohning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Aerts, Marc
2fe1344f-69b0-442d-b4ab-cc5811775e3a
January 2016
Jaspers, Stijn
25595386-1f13-494a-82a6-f48dfff0e9a0
Verbeke, Geert
6ff74f99-0e82-4183-a97d-8bbf0b6708bb
Bohning, Dankmar
1df635d4-e3dc-44d0-b61d-5fd11f6434e1
Aerts, Marc
2fe1344f-69b0-442d-b4ab-cc5811775e3a
Jaspers, Stijn, Verbeke, Geert, Bohning, Dankmar and Aerts, Marc
(2016)
Application of the Vertex Exchange Method to estimate a semi-parametric mixture model for the MIC density of Escherichia coli isolates tested for susceptibility against ampicillin.
Biostatistics, 17 (1), .
(doi:10.1093/biostatistics/kxv030).
Abstract
In the last decades, considerable attention has been paid to the collection of antimicrobial resistance data, with the aim of monitoring non-wild-type isolates. This monitoring is performed based on minimum inhibition concentration (MIC) values, which are collected through dilution experiments. We present a semi-parametric mixture model to estimate the entire MIC density on the continuous scale. The parametric first component is extended with a non-parametric second component and a new back-fitting algorithm, based on the Vertex Exchange Method, is proposed. Our data example shows how to estimate the MIC density for Escherichia coli tested for ampicillin and how to use this estimate for model-based classification. A simulation study was performed, showing the promising behavior of the new method, both in terms of density estimation as well as classification.
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Accepted/In Press date: 14 July 2015
e-pub ahead of print date: 13 August 2015
Published date: January 2016
Organisations:
Statistics, Statistical Sciences Research Institute
Identifiers
Local EPrints ID: 390384
URI: http://eprints.soton.ac.uk/id/eprint/390384
ISSN: 1465-4644
PURE UUID: 716a4079-63a6-4dc7-a004-a3420ef6d373
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Date deposited: 01 Apr 2016 09:17
Last modified: 15 Mar 2024 03:39
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Author:
Stijn Jaspers
Author:
Geert Verbeke
Author:
Marc Aerts
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