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Application of a Bayesian modelling approach to Campylobacter survey data could help the prediction of true prevalence in absence of a gold-standard detection method

Ihab Habib (UGent) , Imca Sampers (UGent) , Mieke Uyttendaele (UGent) , Dirk Berkvens (UGent) and Lieven De Zutter (UGent)
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Chicago
Habib, Ihab, Imca Sampers, Mieke Uyttendaele, Dirk Berkvens, and Lieven De Zutter. 2008. “Application of a Bayesian Modelling Approach to Campylobacter Survey Data Could Help the Prediction of True Prevalence in Absence of a Gold-standard Detection Method.” In Food Micro, Abstracts.
APA
Habib, I., Sampers, I., Uyttendaele, M., Berkvens, D., & De Zutter, L. (2008). Application of a Bayesian modelling approach to Campylobacter survey data could help the prediction of true prevalence in absence of a gold-standard detection method. Food Micro, Abstracts. Presented at the 21st International ICFMH Symposium (Food Micro 2008) : Evolving microbial food quality and safety.
Vancouver
1.
Habib I, Sampers I, Uyttendaele M, Berkvens D, De Zutter L. Application of a Bayesian modelling approach to Campylobacter survey data could help the prediction of true prevalence in absence of a gold-standard detection method. Food Micro, Abstracts. 2008.
MLA
Habib, Ihab, Imca Sampers, Mieke Uyttendaele, et al. “Application of a Bayesian Modelling Approach to Campylobacter Survey Data Could Help the Prediction of True Prevalence in Absence of a Gold-standard Detection Method.” Food Micro, Abstracts. 2008. Print.
@inproceedings{952607,
  author       = {Habib, Ihab and Sampers, Imca and Uyttendaele, Mieke and Berkvens, Dirk and De Zutter, Lieven},
  booktitle    = {Food Micro, Abstracts},
  language     = {eng},
  location     = {Aberdeen, Scotland, UK},
  title        = {Application of a Bayesian modelling approach to Campylobacter survey data could help the prediction of true prevalence in absence of a gold-standard detection method},
  year         = {2008},
}