Local spatial variations analysis of smear-positive tuberculosis in Xinjiang using Geographically Weighted Regression model
Abstract
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 of TB cases and their relevant socioeconomic determinants, thereby forecasting local regression coefficients for the relations between the incidence of TB and its...
Paper Details
Title
Local spatial variations analysis of smear-positive tuberculosis in Xinjiang using Geographically Weighted Regression model
Published Date
Oct 6, 2016
Journal
Volume
16
Issue
1
Citation AnalysisPro
You’ll need to upgrade your plan to Pro
Looking to understand the true influence of a researcher’s work across journals & affiliations?
- Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
- Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.
Notes
History