A Bayesian Maximum Entropy approach to address the change of support problem in the spatial analysis of childhood asthma prevalence across North Carolina.
Lee
Seung-Jae
SJ
Strategic Energy Analysis Center, National Renewable Energy Laboratory, Golden, CO, USA.
Yeatts
Karin B
KB
Serre
Marc L
ML
D017677:Age Distribution; D000397:Air Pollution / Q000009:adverse effects*; D001249:Asthma / Q000175:diagnosis / Q000453:epidemiology*; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D019277:Entropy; D004781:Environmental Exposure / Q000009:adverse effects*; D004784:Environmental Monitoring / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D009657:North Carolina / Q000453:epidemiology; D015995:Prevalence; D018570:Risk Assessment; D012720:Severity of Illness Index; D017678:Sex Distribution; D062206:Spatial Analysis
BME; Geostatistics; asthma; data uncertainty; observation scales