Using a Bayesian change-point statistical model with autoregressive terms to study the monthly number of dispensed asthma medications by public health services

Martinez, Edson Santos Previdelli, Isolde Terezinha Marques de Mello, Luane Casale Aragon, Davi Mota de Queiroz, José André

Descripció:

In this paper, it is proposed a Bayesian analysis of a time series in the presence of a random change-point and autoregressive terms. The development of this model was motivated by a data set related to the monthly number of asthma medications dispensed by the public health services of Ribeirão Preto, Southeast Brazil, from 1999 to 2011. A pronounced increase trend has been observed from 1999 to a specific change-point, with a posterior decrease until the end of the series. In order to obtain estimates for the parameters of interest, a Bayesian Markov Chain Monte Carlo (MCMC) simulation procedure using the Gibbs sampler algorithm was developed. The Bayesian model with autoregressive terms of order 1 fits well to the data, allowing to estimate the change-point at July 2007, and probably reflecting the results of the new health policies and previously adopted programs directed toward patients with asthma. The results imply that the present model is useful to analyse the monthly number of dispensed asthma medications and it can be used to describe a broad range of epidemiological time series data where a change-point is present.

Cobertura:

eng

Títol:

Using a Bayesian change-point statistical model with autoregressive terms to study the monthly number of dispensed asthma medications by public health services

Matèria:

Time series, regression models, Bayesian methods, change-point model, epidemiological data

Format:

application/pdf

Autor:

Martinez, Edson
Santos Previdelli, Isolde Terezinha
Marques de Mello, Luane
Casale Aragon, Davi
Mota de Queiroz, José André

Tipus:

SORT:ART
info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/article

Data:

2018

Editor:

Universitat Rovira i Virgili
Universitat de Lleida
Universitat de Girona
Universitat Pompeu Fabra
Universitat Politècnica de Catalunya
Universitat Autònoma de Barcelona
Universitat de Barcelona
Institut d'Estadística de Catalunya

Autor/s de la URV:	Martinez, Edson Santos Previdelli, Isolde Terezinha Marques de Mello, Luane Casale Aragon, Davi Mota de Queiroz, José André
Any de publicació de la revista:	2018

Informació