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Computational and Mathematical Methods in Medicine
Volume 2016, Article ID 7878325, 7 pages
http://dx.doi.org/10.1155/2016/7878325
Research Article

Analysis of Blood Transfusion Data Using Bivariate Zero-Inflated Poisson Model: A Bayesian Approach

1Student’s Research Committee, Shahrekord University of Medical Sciences, Shahrekord, Iran
2Social Health Determinants Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran
3Epidemiology and Biostatistics Department, Shahrekord University of Medical Sciences, Shahrekord, Iran

Received 14 April 2016; Accepted 16 August 2016

Academic Editor: Dong Song

Copyright © 2016 Tayeb Mohammadi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Recognizing the factors affecting the number of blood donation and blood deferral has a major impact on blood transfusion. There is a positive correlation between the variables “number of blood donation” and “number of blood deferral”: as the number of return for donation increases, so does the number of blood deferral. On the other hand, due to the fact that many donors never return to donate, there is an extra zero frequency for both of the above-mentioned variables. In this study, in order to apply the correlation and to explain the frequency of the excessive zero, the bivariate zero-inflated Poisson regression model was used for joint modeling of the number of blood donation and number of blood deferral. The data was analyzed using the Bayesian approach applying noninformative priors at the presence and absence of covariates. Estimating the parameters of the model, that is, correlation, zero-inflation parameter, and regression coefficients, was done through MCMC simulation. Eventually double-Poisson model, bivariate Poisson model, and bivariate zero-inflated Poisson model were fitted on the data and were compared using the deviance information criteria (DIC). The results showed that the bivariate zero-inflated Poisson regression model fitted the data better than the other models.