首页> 外文会议>Meeting of The Society for Veterinary Epidemiology and Preventive Medicine >RANDOM EFFECT SELECTION IN GENERALISED LINEAR MODELS: A PRACTICAL APPLICATION TO SLAUGHTERHOUSE SURVEILLANCE DATA INDENMARK
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RANDOM EFFECT SELECTION IN GENERALISED LINEAR MODELS: A PRACTICAL APPLICATION TO SLAUGHTERHOUSE SURVEILLANCE DATA INDENMARK

机译:广义线性模型中的随机效应选择:屠宰监视数据indenmark的实际应用

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We analysed abattoir recordings of meat inspection codes with possible relevance to on-farm 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 prevalenceestimates. 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.
机译:我们分析了肉类检测代码的Abattoir记录,可能与牛农场动物福利有关。 随机效应逻辑回归模型用于描述从丹麦屠宰的461,406牛获得的单独数据。 我们的结果表明,最大的差异分区是大多数代码的农场层面,但在Abattoirs之间的一些肉类检查代码报告存在大量变化。 对各个Abattoirs内不同屠宰规范的相对或过度报告也有很大的协议。 这表明丹麦的常规监测的敏感性受Abattorirs之间的工作实践的差异的影响,导致偏见率敏捷。 因此,对于在有意义的推理之前,可以根据肉类检测的数据进行有意义的推断,对Abattoir之间的报告变异来说是必要的。

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