Bayesian estimation of cluster-level test accuracy based on different sampling schemes |
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| Authors: | Chun-Lung Su Ian A. Gardner Wesley O. Johnson |
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| Affiliation: | (1) Department of Disease Control and Epidemiology, National Veterinary Institute, SE-751 89 Uppsala, Sweden;(2) Department of Biomedical Sciences and Veterinary Public Health, Swedish University of Agricultural Sciences, Box 7028, SE-750 07 Uppsala, Sweden;(3) Geoinformatics, Royal Institute of Technology, SE-100 44 Stockholm, Sweden;(4) Department of Animal Environment and Health, Swedish University of Agricultural Sciences, Box 7084, SE-750 07 Uppsala, Sweden |
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| Abstract: | We develop Bayesian models to estimate cluster-level test characteristics, sensitivity, specificity, prevalence, and predictive values, based on four different sampling schemes: a single test case and three sequential test cases. The corresponding cluster-level characteristics are calculated and compared for different sample sizes, sampling schemes, individual-level sensitivities, specificities, and cut-off values. We compared posterior estimates of individual-level and cluster-level characteristics for these four sampling schemes with simulated data. Two illustrations, one for Johne’s disease in cattle and another for Salmonella in pig herds, are used to demonstrate application of the methods. |
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