Empirical Bayes procedures for stabilizing maps of U.S. cancer mortality rates.
"The geographic mapping of age-standardized, cause-specific death rates is a powerful tool for identifying possible etiologic factors, because the spatial distribution of mortality risks can be examined for correlations with the spatial distribution of disease-specific risk factors. This article presents a two-stage empirical Bayes procedure for calculating age-standardized cancer death rates, for use in mapping, which are adjusted for the stochasticity of rates in small area populations. Using the adjusted rates helps isolate and identify spatial patterns in the rates. The model is applied to sex-specific data on U.S. county cancer mortality in the white population for 15 cancer sites for three decades: 1950-1959, 1960-1969, and 1970-1979. Selected results are presented as maps of county death rates for white males."
Duke Scholars
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Related Subject Headings
- White People
- United States
- Statistics & Probability
- Sex Factors
- Population Dynamics
- Population Characteristics
- Population
- North America
- Neoplasms
- Mortality
Citation
Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- White People
- United States
- Statistics & Probability
- Sex Factors
- Population Dynamics
- Population Characteristics
- Population
- North America
- Neoplasms
- Mortality