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Variance estimation for population attributable risk in a complex cross-sectional animal health survey
B A Wagner1, S J Wells, P S Kott
1US Department of Agriculture, Animal and Plant Health Inspection Service, Veterinary Services, Centers for Epidemiology and Animal Health, 555 S. Howes St, Fort Collins, CO 80521, USA. bruce.wagner@usda.gov
Abstract:
Population attributable risk estimates offer a method of combining information on population exposure and disease risk factors into a single measure. Univariate and multivariable methods exist for calculating point estimates and variances under the assumption of equal sampling probabilities. National Animal Health Monitoring System national studies typically use a complex survey design (where selection probabilities vary by design strata), which makes use of these methods of calculating variance inappropriate. We suggest the use of a method called "delete-a-group" jackknife to estimate the variance of population attributable risk when a complex survey design has been implemented. We demonstrate the method using an example of Johne's disease. Advantages of the "delete-a-group" jackknife method include simplicity of implementation and flexibility to estimate variance for any point estimate of interest.
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