The population attributable fraction (PAF) is a useful measure for quantifying the impact of exposure to certain risk factors on a particular outcome at the population level. Recently, new model-based methods for the estimation of PAF and its confidence interval for different types of outcomes in a cohort study design have been proposed. In this paper, we introduce SAS macros implementing these methods and illustrate their application with a data example on the impact of different risk factors on type 2 diabetes incidence.
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Laaksonen et al. (2011) studied this question.
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