流行病學研究所;Graduate Institute of EpidemiologyCHEN, CHIEN-JENCHIEN-JENCHEN2008-10-012018-06-292008-10-012018-06-292006http://ntur.lib.ntu.edu.tw//handle/246246/82053An important component of quantitative risk assessment involves characterizing the dose-response relationship between an environmental exposure and adverse health outcome and then computing a benchmark dose, or the exposure level that yields a suitably low risk. This task is often complicated by model choice considerations, because risk estimates depend on the model parameters. We pro pose using Bayesian methods to address the problem of model selection and derive a model-averaged version of the benchmark dose. We illustrate the methods through application to data on arsenic-induced lung cancer from Taiwan.en-USdose-response modelgeneralized linear modelmodel uncertaintyquantitative risk assessment[SDGs]SDG3journal article