Empirical Bayes Procedures for Stabilizing Maps of U.S. Cancer Mortality Rates
提出两阶段经验贝叶斯方法，调整小区域人群癌症死亡率的随机波动，用于更清晰地识别美国县级癌症死亡率的空间模式，对流行病学和公共卫生研究者有用。
Abstract 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.