Barton C N, Braunberg R C, Friedman L
Division of Mathematics, U.S. Food and Drug Administration, Washington, D.C. 20204.
Biometrics. 1993 Mar;49(1):95-105.
A general approach using nonlinear regression models is presented for evaluating additivity, synergism, and antagonism of mixtures of toxins for proportions and ratio-scale response measures. This approach provides several advantages over the analysis methods typically used, which involve linear regression with logits or probits. A single model fit is performed, rather than a multistep procedure. Nonadditive alternative models can be easily constructed and tested against the appropriate additive models. The approach avoids the use of data "adjustments" for nonzero background response rates. The analyses are performed in the natural response metric, making interpretation straightforward. Also, the nonlinear regression model can be reparameterized to provide more meaningful primary parameters.
本文提出了一种使用非线性回归模型的通用方法，用于评估毒素混合物对于比例和比率尺度反应指标的相加性、协同性和拮抗作用。与通常使用的分析方法（涉及对数单位或概率单位的线性回归）相比，该方法具有多个优点。它只需进行一次模型拟合，而不是多步骤过程。非相加性替代模型可以轻松构建并针对适当的相加性模型进行检验。该方法避免了对非零背景反应率进行数据“调整”。分析在自然反应度量中进行，使得解释直接明了。此外，非线性回归模型可以重新参数化以提供更有意义的主要参数。
