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Using a Bayesian change-point statistical model with autoregressive terms to study the monthly number of dispensed asthma medications by public health services
Mota de Queiroz, J. A. (Instituto Federal do Paraná – IFPR (Brasil))
Aragon, Davi Casale (Universidade de São Paulo. Ribeirão Preto Medical School)
Mello, Luane Marques de (Universidade de São Paulo. Ribeirão Preto Medical School)
Previdelli, Isolde Terezinha Santos (Universidade Estadual de Maringá)
Martinez, Edson Z. (Universidade de São Paulo. Ribeirão Preto Medical School)

Data: 2018
Resum: 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 Ribeirao 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.
Drets: Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial 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. Creative Commons
Llengua: Anglès.
Document: article ; recerca ; publishedVersion
Matèria: Time series ; Regression models ; Bayesian methods ; Change-point model ; Epidemiological data
Publicat a: SORT : statistics and operations research transactions, Vol. 42 Núm. 1 (January-June 2018) , p. 3-26 (Articles) , ISSN 1696-2281

Adreça original: https://www.raco.cat/index.php/SORT/article/view/338204
DOI: 10.2436/20.8080.02.66


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 Registre creat el 2018-06-26, darrera modificació el 2018-08-06



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