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A multivariate space-time model for analysing county level heart disease death rates by race and sex
Journal article   Open access

A multivariate space-time model for analysing county level heart disease death rates by race and sex

Harrison Quick, Lance A. Waller and Michele Casper
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS, v 67(1), pp 291-304
01 Jan 2018
url
http://arxiv.org/abs/1507.02741View

Abstract

Mathematics Physical Sciences Science & Technology Statistics & Probability
Although death rates from heart disease have declined sharply over the past 50 years, the rate of decline varies by location, race and sex. Despite these declines, heart disease continues to be the leading cause of death in the USA. We propose a non-separable multivariate spatiotemporal Bayesian model to obtain a clearer picture of the temporally varying trends in county level heart disease death rates for men and women of different races in the USA. After verifying the effectiveness of our model via simulation, we apply our model to a data set of over 230000 county level heart disease death rates.

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30 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#3 Good Health and Well-Being

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Collaboration types
Domestic collaboration
Web of Science research areas
Statistics & Probability
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