In this paper we present a Bayesian model to analyze sequences of hospitalizations of patients affected by chronic heart disease, focusing not only on the sequence but also on the times between two next events; considering covariates and time, the model is able to identify the most relevant factors influencing the evolution. © Springer International Publishing Switzerland 2014.

Analysis of hospitalizations of patients affected by chronic heart disease

A Guglielmi;R Argiento
2014

Abstract

In this paper we present a Bayesian model to analyze sequences of hospitalizations of patients affected by chronic heart disease, focusing not only on the sequence but also on the times between two next events; considering covariates and time, the model is able to identify the most relevant factors influencing the evolution. © Springer International Publishing Switzerland 2014.
2014
Istituto di Matematica Applicata e Tecnologie Informatiche - IMATI -
Inglese
Ettore Lanzarone; Francesca Ieva
The contribution of young researchers to Bayesian statistics: Proceedings of BAYSM2013
First Bayesian Young Statistician Meeting (BAYSM 2013)
63
155
159
978-3-319-02083-9
http://link.springer.com/book/10.1007%2F978-3-319-02084-6
Springer
Cham Heidelberg New York Dordrecht London
SVIZZERA
5-6/06/2013
Milano
Heart disease
hospitalizations
2
none
A. Parodi; F. Ieva; A. Guglielmi;R. Argiento
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/257797
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