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Enhancing the interpretation of statistical P values in toxicology studies: implementation of linear mixed models (LMMs) and standardized effect sizes (SESs)

机译:加强毒理学研究中统计P值的解释:线性混合模型(LMM)和标准化效应量(SES)的实现

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摘要

In this paper, we compare the traditional ANOVA approach to analysing data from 90-day toxicity studies with a more modern LMM approach, and we investigate the use of standardized effect sizes. The LMM approach is used to analyse weight or feed consumption data. When compared to the week-by-week ANOVA with multiple test results per week, this approach results in only one statement on differences in weight development between groups. Standardized effect sizes are calculated for the endpoints: weight, relative organ weights, haematology and clinical biochemistry. The endpoints are standardized, allowing different endpoints of the same study to be compared and providing an overall picture of group differences at a glance. Furthermore, in terms of standardized effect sizes, statistical significance and biological relevance are displayed simultaneously in a graph.
机译:在本文中,我们将传统的ANOVA方法与90天毒性研究的数据与更现代的LMM方法进行了比较,并研究了标准化效应量的使用。 LMM方法用于分析重量或饲料消耗数据。当与每周进行多次测试的每周方差分析进行比较时,这种方法只能得出一组之间体重发展差异的陈述。计算终点的标准化效应量:体重,相对器官重量,血液学和临床生物化学。终点是标准化的,因此可以比较同一研究的不同终点,并一目了然地提供群体差异的总体情况。此外,就标准化效应大小而言,统计显着性和生物学相关性在图表中同时显示。

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