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."
Manton
K G
KG
Woodbury
M A
MA
Stallard
E
E
Riggan
W B
WB
Creason
J P
JP
Pellom
A C
AC
D000367:Age Factors; D000569:Americas; D002423:Cause of Death; D003469:Culture; D003710:Demography; D019049:Developed Countries; D004194:Disease; D005006:Ethnicity; D005843:Geography; D008377:Maps as Topic; D008722:Methods; D009026:Mortality; D009369:Neoplasms; D009656:North America; D011153:Population; D011154:Population Characteristics; D011157:Population Dynamics; D012737:Sex Factors; D014481:United States; D044465:White People
Age Factors; Americas; Cancer; Causes Of Death; Cultural Background; Death Rate; Demographic Factors; Developed Countries; Diseases; Ethnic Groups; Geographic Factors; Maps; Methodological Studies; Mortality; Neoplasms; North America; Northern America; Population; Population Characteristics; Population Dynamics; Sex Factors; Spatial Distribution; United States; Whites