1. Sample size calculations for Bayesian prediction of bovine viral-diarrhoea-virus infection in beef herds.
- Author
-
Huzurbazar S, Van Campen H, and McLean MB
- Subjects
- Animals, Cattle, Diarrhea Viruses, Bovine Viral, Prevalence, Wyoming epidemiology, Bayes Theorem, Bovine Virus Diarrhea-Mucosal Disease epidemiology, Bovine Virus Diarrhea-Mucosal Disease prevention & control
- Abstract
We used a Bayesian classification approach to predict the bovine viral-diarrhoea-virus infection status of a herd when the prevalence of persistently infected animals in such herds is very small (e.g. <1%). An example of the approach is presented using data on beef herds in Wyoming, USA. The approach uses past covariate information (serum-neutralization titres collected on animals in 16 herds) within a predictive model for classification of a future observable herd. Simulations to estimate misclassification probabilities for different misclassification costs and prevalences of infected herds can be used as a guide to the sample size needed for classification of a future herd.
- Published
- 2004
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