Bayesian correlated models for assessing the prevalence of viruses in organic and non-organic agroecosystems
Lázaro, Elena (Universitat de València. Departament d'Estadística i Investigació Operativa)
Armero, Carmen (Universitat de València. Departament d'Estadística i Investigació Operativa)
Rubio, Luis (Instituto Valenciano de Investigaciones Agrarias)

Data:	2017
Resum:	Cultivation of horticultural species under organic management has increased in importance in recent years. However, the sustainability of this new production method needs to be supported by scientific research, especially in the field of virology. We studied the prevalence of three important virus diseases in agroecosystems with regard to its management system: organic versus non-organic, with and without greenhouse. Prevalence was assessed by means of a Bayesian correlated binary model which connects the risk of infection of each virus within the same plot and was defined in terms of a logit generalized linear mixed model (GLMM). Model robustness was checked through a sensitivity analysis based on different hyperprior scenarios. Inferential results were examined in terms of changes in the marginal posterior distributions, both for fixed and for random effects, through the Hellinger distance and a derived measure of sensitivity. Statistical results suggested that organic systems show lower or similar prevalence than non-organic ones in both single and multiple infections as well as the relevance of the prior specification of the random effects in the inferential process.
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Hellinger distance ; Model robustness ; Risk infection ; Sensitivity analysis ; Virus epidemiology
Publicat a:	SORT : statistics and operations research transactions, Vol. 41 Núm. 1 (January-June 2017) , p. 93-116 (Articles) , ISSN 2013-8830

Adreça alternativa: https://raco.cat/index.php/SORT/article/view/326050
DOI: 10.2436/20.8080.02.52

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