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Updated: Jun 21, 2026

An R-Based Landscape Validation of a Competing Risk Model
Published on: September 16, 2022
[Utilization of fully Bayesian modeling to detect patterns in relative risk variation for infant mortality in Rio
Sérgio Kakuta Kato1, Diego de Matos Vieira, Jandyra Maria Guimarães Fachel
1Faculdade de Matemática, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brasil. klmsergio@terra.com.br
Abstract:
The infant mortality rate is one of the key indicators used to measure a population's quality of life. The State of Rio Grande do Sul has a social and economic indicator called the Socioeconomic Development Index (IDESE). Most studies analyze the infant mortality rate in relation to risk factors, visually aided by maps. This study presents the methodology and an application of a Spatial Epidemiology method called the ecological correlation, using hierarchical Bayesian procedures. The article discusses the main problems found in ecological correlations, such as spatial autocorrelation and the estimator's instability for small areas. To overcome these difficulties, the relative risk estimate obtained by spatial regression analysis using fully Bayesian estimation is presented. The infant mortality rate is analyzed in all 496 municipalities of Rio Grande do Sul for the years 2001 to 2004. Several models with spatial component and different variables from the IDESE/2003 were compared. The model using spatial structure along with the variable 'education' was considered the best choice. With this methodology, it was possible to obtain a more interpretable pattern of infant mortality risk in Rio Grande do Sul.
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