Local spatial variations analysis of smear-positive tuberculosis in Xinjiang using Geographically Weighted Regression model

Local spatial variations analysis of smear-positive tuberculosis in Xinjiang using Geographically Weighted Regression model

Abstract Background The spatial interplay between socioeconomic factors and tuberculosis (TB) cases contributes to the understanding of regional tuberculosis burdens. Historically, local Poisson Geographically Weighted Regression (GWR) has allowed for the identification of the geographic disparities...

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Bibliographic Details
Main Authors: Wang Wei, Jin Yuan-Yuan, Yan Ci, Alayi Ahan, Cao Ming-Qin
Format: Article
Language:English
Published: BMC 2016-10-01
Series:BMC Public Health
Subjects:
Tuberculosis
Ordinary least square regression model
Geographically weighted regression model
Local spatial variations
Online Access:http://link.springer.com/article/10.1186/s12889-016-3723-4

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http://link.springer.com/article/10.1186/s12889-016-3723-4

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