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评估生化分析中的不精密度概况。

Estimating imprecision profiles in biochemical analysis.

作者信息

Berweger C D, Müller-Plathe F, Hänseler E, Keller H

机构信息

Laboratorium für Physikalische Chemie, Eidgenössische Technische Hochschule Zürich, ETH Zentrum, Switzerland.

出版信息

Clin Chim Acta. 1998 Oct;277(2):107-25. doi: 10.1016/s0009-8981(98)00093-x.

Abstract

We describe a computer program IMPROFIL which determines an imprecision profile of an analytical method from replicated measurements of samples. It calculates the variance function, the coefficient of variation, the power of definition, the critical limit, the limit of detection and the lower limit of quantification. The primary property, the variance function, is determined by two alternative methods: the conventional maximum approximate conditional likelihood method and the newly developed weighted absolute deviation method. For all quantities, confidence intervals are obtained using the bootstrap procedure. The program combines the use of robust numerical techniques, user-friendliness and integration into a spreadsheet program for data pre- and post-processing. The algorithms used are described in detail. Tests with synthetic data sets are used to validate the method and to establish its powers and limitations. Finally, its application to a practical analytical task (tumor marker CA 15-3 in human sera) is reported. For the method to yield a reliable estimate of the variance function and the derived properties, certain minimum requirements on the raw data must be met: They have to be spread throughout the concentration range of interest, there should not be less than three replicates per specimen, and there must be at least of the order of 25 (better at 50) specimens.

摘要

我们描述了一个名为IMPROFIL的计算机程序,它可根据对样品的重复测量来确定分析方法的不精密度概况。该程序能计算方差函数、变异系数、定义功效、临界限度、检测限和定量下限。其主要属性,即方差函数,可通过两种替代方法来确定:传统的最大近似条件似然法和新开发的加权绝对偏差法。对于所有这些量,可使用自助法获得置信区间。该程序结合了稳健数值技术的应用、用户友好性以及与电子表格程序的集成,用于数据的预处理和后处理。文中详细描述了所使用的算法。通过对合成数据集进行测试来验证该方法,并确定其能力和局限性。最后,报告了该方法在一项实际分析任务(人血清中的肿瘤标志物CA 15-3)中的应用。为使该方法对方差函数及派生属性得出可靠估计,原始数据必须满足某些最低要求:它们必须分布在感兴趣的浓度范围内,每个样本的重复测量次数不应少于三次,且样本数量必须至少约为25个(50个更好)。

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