Peer-Reviewed Journal Details
Mandatory Fields
Ferguson, J,Alvarez-Iglesias, A,Newell, J,Hinde, J,O'Donnell, M
2016
April
Statistical Methods In Medical Research
Estimating average attributable fractions with confidence intervals for cohort and case-control studies
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Epidemiology attributable fraction permutations weighted likelihood Monte Carlo confidence interval RISK-ESTIMATION POPULATION DISEASES
27
1141
1152
Chronic diseases tend to depend on a large number of risk factors, both environmental and genetic. Average attributable fractions were introduced by Eide and Gefeller as a way of partitioning overall disease burden into contributions from individual risk factors; this may be useful in deciding which risk factors to target in disease interventions. Here, we introduce new estimation methods for average attributable fractions that are appropriate for both case-control designs and prospective studies. Confidence intervals, derived using Monte Carlo simulation, are also described. Finally, we introduce a novel approximation for the sample average attributable fraction that will ensure a computationally tractable approach when the number of risk factors is large. An R package, averisk, implementing the methods described in this manuscript can be downloaded from the CRAN repository.
10.1177/0962280216655374
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