Bayesian Smoothing of Lung Cancer Data in Tirol, Salzburg and Vorarlberg
DOI:
https://doi.org/10.17713/ajs.v28i1.507Abstract
Due to the high variability ofML-estimates of relative risk in low population areas incidence ratios have to be smoothed before mapping. We fit a Bayesian hierarchical model where the posterior distribution of relative risks is simulated via a Markov Chain Monte Carlo technique.References
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