Regression methods for the analysis of paired measurements produced by two fallible assay methods are described and their advantages and pitfalls discussed. The difficulties for the analysis, as in any errors-in-variables problem lies in the lack of identifiability of the model and the need to introduce questionable and often naïve assumptions in order to gain identifiability. Although not a panacea, the use of instrumental variables and associated instrumental variable (IV) regression methods in this area of application has great potential to improve the situation. Large samples are frequently needed and two-phase sampling methods are introduced to improve the efficiency of the IV estimators.

译文

:描述了用于分析由两种易失分析方法产生的配对测量值的回归方法,并讨论了它们的优点和陷阱。像任何变量误差问题一样,分析的困难在于缺乏模型的可识别性,并且需要引入可疑且通常为幼稚的假设以获取可识别性。尽管不是万能药,但在此应用领域中使用工具变量和相关的工具变量(IV)回归方法具有改善这种情况的巨大潜力。经常需要大样本,并且引入了两阶段采样方法以提高IV估计器的效率。

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