Additive Bayesian networks (ABNs) are types of graphical models that extend the usual generalized linear model (GLM) to multiple dependent variables through the representation of joint probability distribution. Thanks to their flexible properties, ABNs have been widely used in epidemiological analyses. In this work we present a veterinary case study where ABNs are used to explore multivariate swine diseases data of medical relevance. We then compare the results with a classical methodology. Finally, we highlight the key difference between a multivariable standard (GLM) and a multivariate (ABN) approach: the latter attempts not only to identify statistically associated variables, but also to additionally separate these into those directly and indirectly dependent with one or more outcome variables.

Additive Bayesian networks for an epidemiological analysis of swine diseases / Marta Pittavino; Reinhard Furrer. - ELETTRONICO. - (2018), pp. 1160-1165. (Intervento presentato al convegno 49th Meeting of the Italian Statistical Society).

Additive Bayesian networks for an epidemiological analysis of swine diseases

Marta Pittavino
;
2018

Abstract

Additive Bayesian networks (ABNs) are types of graphical models that extend the usual generalized linear model (GLM) to multiple dependent variables through the representation of joint probability distribution. Thanks to their flexible properties, ABNs have been widely used in epidemiological analyses. In this work we present a veterinary case study where ABNs are used to explore multivariate swine diseases data of medical relevance. We then compare the results with a classical methodology. Finally, we highlight the key difference between a multivariable standard (GLM) and a multivariate (ABN) approach: the latter attempts not only to identify statistically associated variables, but also to additionally separate these into those directly and indirectly dependent with one or more outcome variables.
2018
Book of Short Papers SIS 2018
49th Meeting of the Italian Statistical Society
Marta Pittavino; Reinhard Furrer
File in questo prodotto:
File Dimensione Formato  
P12_BookOfShortPapersSIS49Conference_ABNforEpiAnalysisSwineDisease.pdf

accesso aperto

Tipologia: Pdf editoriale (Version of record)
Licenza: Open Access
Dimensione 149.02 kB
Formato Adobe PDF
149.02 kB Adobe PDF

I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1322122
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? ND
social impact