Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/16236
Title: Adaptive change-point mixed models applied to data on outpatient tetracycline use in Europe
Authors: AYELE, Girma 
AERTS, Marc 
Coenen, Samuel
Versporten, Ann
Muller, Arno
Adriaenssens, Niels
Beutels, Philippe
MOLENBERGHS, Geert 
Goossens, Herman
HENS, Niel 
Issue Date: 2013
Source: STATISTICAL MODELLING, 13 (3), p. 253-274
Abstract: In this paper, we propose a change-point mixed model to assess the change in the trend of outpatient antibiotic use in a Bayesian framework, where the change-points are unknown parameters of the model. Model selection using DIC indicates that the data supports the model with a country-specific change-point. The location of the change-points may be related to points in time where public health strategies aiming at increasing the awareness of the public to a more rational use of antibiotics or targeting to reduce overconsumption of antibiotics were initiated.
Keywords: amplitude; antibiotice use; change-point model; non-mlinear model; phase shift; scasonal variation
Document URI: http://hdl.handle.net/1942/16236
ISSN: 1471-082X
e-ISSN: 1477-0342
DOI: 10.1177/1471082X13485404
ISI #: 000320228900004
Rights: (C) 2013 SAGE Publications
Category: A1
Type: Journal Contribution
Validations: ecoom 2014
Appears in Collections:Research publications

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