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An introduction of smoothing incidence rates by penalized likelihood
1Department of Mathematics, Statistics and Computing Science, Dalhousie University, Halifax, Nova Scotia, Canada.
Abstract:
Most recent developments in the smoothing of disease incidence rates have involved empirical Bayes procedures. Through the introduction of an intersite distance penalty, the pooling of information by directly penalizing the maximum likelihood estimates is proposed. A distance type statistic tests a null hypothesis of homogeneity among the rates and is applied to gastric cancer incidence of Nova Scotia municipalities. For various spatial patterns, simulation results are presented which investigate the power of the test, the total mean squared error and the distribution of the smoothed estimates.
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