Estimating spatial variation in disease risk from locations coarsened by incomplete geocoding

DOI10.1016/J.STAMET.2011.01.008zbMath1248.62224OpenAlexW2033930059MaRDI QIDQ713945

Xiangming Fang, Dale L. Zimmerman

Publication date: 19 October 2012

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2011.01.008

zbMATH Keywords

relative riskcoarsened dataspatial epidemiology

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05)

Cites Work

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• Kernel estimation of relative risk
• Analyzing spatial point patterns subject to measurement error
• Intensity Estimation for Spatial Point Processes Observed with Noise
• A Kernel Method for Smoothing Point Process Data
• Spatial Variation in Risk of Disease: A Nonparametric Binary Regression Approach
• Applied Spatial Statistics for Public Health Data
• Ignorability and Coarse Data: Some Biomedical Examples
• Estimating the Intensity of a Spatial Point Process from Locations Coarsened by Incomplete Geocoding
• Homogeneous Linear Predictor Models for Contingency Tables

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