The five-parameter logistic: A characterization and comparison with the four-parameter logistic
The five-parameter logistic: A characterization and comparison with the four-parameter logistic
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DOI：
10.1016/j.ab.2005.04.035
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发表时间：
2005-08-01
影响因子：
2.9
通讯作者：
Dunn, JR
中科院分区：
文献类型：
--
作者：
Gottschalk, PG;Dunn, JR
测定技术的改进已经将测量响应中的随机变化量减少到测定数据的甚至轻微不对称可以比随机变化更显著的程度。使用五参数逻辑（5PL）函数来拟合剂量反应数据很容易适应这种不对称性。与使用对称模型（如四参数逻辑（4PL）函数）相比，5PL可显著提高不对称测定的准确度。然而，直到最近，拟合5PL函数的过程一直很困难，其结果是，即使对于高度不对称的数据，4PL函数也继续被使用。已经开发了4PL方法的各种特别修改，以试图解决不对称数据。然而，数值方法和测定分析软件的最新进展使得5PL例程的拟合变得更容易。本文演示了使用5PL功能如何提高4PL及其变体的检测性能。具体而言，可以使用5PL的4PL作为数据中存在的不对称性的函数获得的浓度估计的准确性的改善进行了研究。讨论了5PL曲线的行为以及它与4PL曲线的不同之处。常见的实验设计，这可能会导致病态回归问题，也检查。(c)2005年爱思唯尔公司All rights reserved.
Improvements in assay technology have reduced the amount of random variation in measured responses to the point where even slight asymmetry of the assay data can be more significant than random variation. Use of the five-parameter logistic (5PL) function to fit dose-response data easily accommodates such asymmetry. The 5PL can dramatically improve the accuracy of asymmetric assays over the use of symmetric models such as the four-parameter logistic (4PL) function. Until recently, however, the process of fitting the 5PL function has been difficult, with the result that the 4PL function has continued to be used even for highly asymmetric data. Various ad hoc modifications of the 4PL method have been developed in an attempt to address asymmetric data. However, recent advances in numerical methods and assay analysis software have rendered easier the fitting of the 5PL routine. This paper demonstrates how use of the 5PL function can improve assay performance over the 4PL and its variants. Specifically, the improvement in the accuracy of concentration estimates that can be obtained using the 5PL over the 4PL as a function of the asymmetry present in the data is studied. The behavior of the 5PL curve and how it differs from the 4PL curve are discussed. Common experimental designs, which can lead to ill-conditioned regression problems, are also examined. (c) 2005 Elsevier Inc. All rights reserved.