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分析方法转移:基于比率的统计方法提高可解释性。

Analytical method transfer: improving interpretability with ratio-based statistical approaches.

机构信息

Institut für Biometrie, Medizinische Hochschule Hannover, Carl-Neuberg-Strasse 1, D-30625 Hannover, Germany.

出版信息

J Pharm Biomed Anal. 2013 Feb 23;74:186-93. doi: 10.1016/j.jpba.2012.10.032. Epub 2012 Nov 5.

Abstract

After assay validation in an originating laboratory, an analytical method needs to be transferred to one or several production laboratories, because measured outcomes among the laboratories must agree. To state agreement, the locations (e.g. means) must be equivalent and the production laboratory must be non-inferior to the originating one concerning scales (e.g. standard deviations). Here, parametric and non-parametric approaches based on marginal confidence intervals for the ratio of locations and the ratio of scales are presented. These intervals are appropriate for a matched pairs design without repeated measurements. Results of simulation studies investigating the power and the control of the type I error are shown and limits of the approaches are discussed. In addition, a Bland-Altman plot with tolerance intervals is proposed. As illustrated in the example proportional differences greatly improve the interpretation of the results compared to absolute differences.

摘要

在原始实验室进行了测定验证后,由于实验室之间的测量结果必须一致,因此需要将分析方法转移到一个或多个生产实验室。为了表示一致性,地点(例如平均值)必须相等,并且生产实验室在规模(例如标准偏差)方面必须不逊于原始实验室。在这里,介绍了基于位置比和比例比的边缘置信区间的参数和非参数方法。这些区间适用于没有重复测量的配对设计。还展示了调查比率和比例的功效和 I 类错误控制的模拟研究结果,并讨论了这些方法的局限性。此外,还提出了带有公差区间的 Bland-Altman 图。如示例所示,与绝对差异相比,比例差异极大地改善了结果的解释。

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