[A new decision tree method for statistical analysis of quantitative data obtained in toxicity studies on rodents].
[A new decision tree method for statistical analysis of quantitative data obtained in toxicity studies on rodents].
复制标题
[一种新的决策树方法，用于对啮齿动物毒性研究中获得的定量数据进行统计分析]。
DOI：
10.1539/sangyoeisei.kj00001991484
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发表时间：
2000
影响因子：
--
通讯作者：
H. Takeuchi
中科院分区：
文献类型：
--
作者：
K. Kobayashi;M. Kanamori;K. Ohori;H. Takeuchi
关于毒性研究中对照组和剂量组获得的定量数据的统计分析，我们试图简化决策树方法。本文提出了一种新的决策树，它将传统决策树中的单因素方差分析和Kruskal-Wallis非参数方差分析排除在外：（1）Bartlett检验用于检验k个方差的相等性;（2）如果k个抽样总体的方差相等，则（通过Bartlett检验，p > 0.05），进行Dunnett多重比较检验;否则，使用Steel检验。这种新方法在某些情况下提高了决策树的功效，可以作为传统决策树方法的一种替代方法。
Regarding the statistical analysis of the quantitative data obtained in control and dosage groups in toxicity studies, we tried to simplify the decision tree method. In a new decision tree presented in this article, one-way analysis of variance and Kruskal-Wallis nonparametric analysis of variance are excluded from the traditional decision tree: (1) Bartlett's test is used as a test for the equality of k variances: (2) Then, if the k sampled populations have equal variances (p > 0.05 by the Bartlett's test), Dunnett's multiple comparison test is performed: otherwise, Steel's test is used. This new method, which increases the power in some conditions, may serve as an alternative to the traditional decision tree method.