Random effect selection in generalised linear models: a practical application to slaughterhouse surveillance data in Denmark
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Documents
- Denwood_SVEPM Proceedings 2015
Final published version, 207 KB, PDF document
We analysed abattoir recordings of meat inspection codes with possible relevance to onfarm animal welfare in cattle. Random effects logistic regression models were used to describe individual-level data obtained from 461,406 cattle slaughtered in Denmark. Our results demonstrate that the largest variance partition was at farm level for most codes, but there was substantial variation in reporting for some meat inspection codes between abattoirs.
There was also substantial agreement for the relative under or over-reporting of different slaughter codes within individual abattoirs. This indicates that the sensitivity of routine surveillance in Denmark is affected by differences in the working practices between abattoirs, resulting in biased prevalence estimates. Therefore, it is essential to correct for the variation in reporting between abattoirs before meaningful inference can be made from prevalence estimates based on data derived from meat inspection.
There was also substantial agreement for the relative under or over-reporting of different slaughter codes within individual abattoirs. This indicates that the sensitivity of routine surveillance in Denmark is affected by differences in the working practices between abattoirs, resulting in biased prevalence estimates. Therefore, it is essential to correct for the variation in reporting between abattoirs before meaningful inference can be made from prevalence estimates based on data derived from meat inspection.
Original language | English |
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Publication date | 26 Mar 2015 |
Number of pages | 11 |
Publication status | Published - 26 Mar 2015 |
Event | Annual Meeting of the Society of Veterinary Epidemiology and Preventive medicine: SVEPM - Ghent, Belgium Duration: 25 Mar 2015 → 27 Mar 2015 |
Conference
Conference | Annual Meeting of the Society of Veterinary Epidemiology and Preventive medicine |
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Country | Belgium |
City | Ghent |
Period | 25/03/2015 → 27/03/2015 |
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