Propensity score matching for multilevel spatial data: accounting for geographic confounding in health disparity studies

Propensity score matching for multilevel spatial data: accounting for geographic confounding in health disparity studies

Abstract Background Diabetes is a public health burden that disproportionately affects military veterans and racial minorities. Studies of racial disparities are inherently observational, and thus may require the use of methods such as Propensity Score Analysis (PSA). While traditional PSA accounts...

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Bibliographic Details
Main Authors: Melanie L. Davis, Brian Neelon, Paul J. Nietert, Lane F. Burgette, Kelly J. Hunt, Andrew B. Lawson, Leonard E. Egede
Format: Article
Language:English
Published: BMC 2021-02-01
Series:International Journal of Health Geographics
Subjects:
Average treatment effect among treated (ATT)
Causal inference
Health disparities
Propensity score matching
Spatial data analysis
Online Access:https://doi.org/10.1186/s12942-021-00265-1

Internet

https://doi.org/10.1186/s12942-021-00265-1

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