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毒理学研究中对啮齿动物体重进行多次邓尼特检验的总体I型错误率和检验效能。

Overall type I error rate and power of multiple Dunnett's tests on rodent body weights in toxicology studies.

作者信息

Hoffman Wherly P, Recknor Justin, Lee Cindy

机构信息

Global Statistical Sciences, Eli Lilly and Company, Indianapolis, Indiana 46285, USA.

出版信息

J Biopharm Stat. 2008;18(5):883-900. doi: 10.1080/10543400802287420.

Abstract

Body weight data are routinely collected in in vivo general toxicology studies, including 2-year carcinogenicity studies, to help assess the overall health of animals. The effect of the compound on body weight is statistically evaluated for each sex separately using a linear trend test or a many-to-one test by Dunnett. These tests are performed either in the framework of a one-factor analysis of variance (ANOVA) or a repeated measures ANOVA. The one-factor ANOVA with Dunnett's test at each time point is a common practice in industry. Although each individual test is conducted at the 0.05 significance level, one wonders about the overall type I error rate and power for performing many individual Dunnett's tests. A simulation study is conducted to answer this question for general toxicology studies of durations 1 month, 3 months, and 2 years. These results provide guidance to managing multiplicity of body weight analysis of general toxicology studies.

摘要

在体内一般毒理学研究中,包括两年致癌性研究,会定期收集体重数据,以帮助评估动物的整体健康状况。使用线性趋势检验或Dunnett的多对一检验,分别对每种性别统计评估化合物对体重的影响。这些检验在单因素方差分析(ANOVA)框架内或重复测量方差分析中进行。在每个时间点使用Dunnett检验的单因素方差分析是行业中的常见做法。尽管每个单独的检验都在0.05的显著性水平上进行,但人们会质疑进行多次单独的Dunnett检验时的总体I型错误率和检验效能。进行了一项模拟研究,以回答关于为期1个月、3个月和2年的一般毒理学研究的这个问题。这些结果为管理一般毒理学研究体重分析的多重性提供了指导。

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