NONLINEAR STATISTICAL-MODELS FOR THE JOINT ACTION OF TOXINS
NONLINEAR STATISTICAL-MODELS FOR THE JOINT ACTION OF TOXINS
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DOI：
10.2307/2532605
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发表时间：
1993-03-01
期刊：
影响因子：
1.9
通讯作者：
FRIEDMAN, L
中科院分区：
文献类型：
--
作者：
BARTON, CN;BRAUNBERG, RC;FRIEDMAN, L
一个一般的方法，使用非线性回归模型的比例和比例尺度的反应措施的毒素的混合物的加和性，协同作用和拮抗作用进行评估。这种方法与通常使用的分析方法相比具有几个优点，通常使用的分析方法涉及使用logits或probit的线性回归。执行单个模型拟合，而不是多步过程。非加性替代模型可以很容易地构建和测试对适当的加性模型。该方法避免了对非零背景响应率使用数据“调整”。分析是在自然反应度量中进行的，使得解释变得简单。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。
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.