Department of Animal Sciences, University of Wisconsin, Madison 53706, USA.
J Anim Sci. 2013 Feb;91(2):553-64. doi: 10.2527/jas.2012-5840. Epub 2012 Dec 10.
Data regularly recorded in commercial herds have been used extensively for estimation of disease incidence rates, for inferences regarding genetic and phenotypic associations between traits, or for developing predictive models for economically important traits. Some studies have also used field data to investigate potential causal relationships between variables. However, inferring causal effects from observational data is complex due to potential confounding effects and careful analyses using specific statistical and data mining techniques as well as different sets of assumptions are required. Nonetheless, although virtually unknown in the agricultural research community, such methods are available and have been used in many other fields. In this paper, we review and discuss the analysis of observational data using field-recorded information and its potential utility in the study of causal effects in livestock. It is our postulation that there is much to be learned from such data, which can be used either to explicitly investigate causal relationships between variables or to generate hypotheses for further investigation using controlled experiments or additional field-recorded data.
商业牛群中定期记录的数据已被广泛用于估计疾病发病率，用于推断性状之间的遗传和表型关联，或用于开发对经济重要性状的预测模型。一些研究也利用现场数据来研究变量之间的潜在因果关系。然而，由于潜在的混杂效应，从观察性数据中推断因果效应是复杂的，需要使用特定的统计和数据挖掘技术以及不同的假设集进行仔细分析。尽管在农业研究界几乎不为人知，但这些方法是可用的，并且已经在许多其他领域中得到了应用。在本文中，我们回顾和讨论了使用现场记录信息进行观察性数据分析及其在研究家畜因果效应中的潜在应用。我们的假设是，从这类数据中可以学到很多东西，这些数据可以用来明确地研究变量之间的因果关系，或者用来生成进一步使用对照实验或额外现场记录数据进行研究的假设。
