Related Experiment Video
Updated: Oct 7, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
Published on: June 26, 2013
Smoothing geographical data, particularly rates of disease
1Department of Mathematics, University of Colorado-Denver 80217-3364, USA.
Abstract:
This paper proposes a linear smoother for geographically-defined data that consist of standardized rates (for example, adjusted for age). The smoother is viewed as a special case of one that applies to data in the form of ratios, and situations are described under which such a smoother can and cannot be useful. Its application to mortality rates due to prostate cancer in both whites and non-whites demonstrates its potential to highlight features in the data that might otherwise remain obscure. Some open questions concerning inference of apparent trends are discussed.
More Related Videos
10:46A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
09:50Real-World M3-BREATHE: Toward Multimodal Mobile Monitoring of Behaviour, Respiration, and Exposures for Treatment and Health Evaluation
Published on: June 5, 2026
Related Concept Videos
Causality in Epidemiology
Bias in Epidemiological Studies
Statistical Methods for Analyzing Epidemiological Data
Principles of Disease Surveillance
Selected Data About Geographic Locations
Linear Approximations