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[药理数据的统计分析:多重比较问题]

[Statistical analysis of pharmacological data: problem of multiple comparison].

作者信息

Hashimoto S

机构信息

Department of Epidemiology and Preventive Sciences, School of Health Sciences and Nursing, University of Tokyo, Japan.

出版信息

Nihon Yakurigaku Zasshi. 1997 Dec;110(6):325-32. doi: 10.1254/fpj.110.325.

Abstract

Problems of multiple comparison were discussed without assuming technical knowledge of statistics. For the first question concerning why to use multiple comparison procedures, theoretical bases of statistical inference and multiple comparison (including type I error rate and familywise error rate) were briefly outlined. For the second question concerning how to properly use multiple comparison procedures, multiple comparison procedures were introduced, and their characteristics were compared. Families of comparisons are different among Dunnett's, Tukey's and Scheffe's tests. Assumptions of dose-response relationship are different among Dunnett's, Williams' tests and linear regression analysis. Duncan's test does not control familywise error rate at a fixed level. For the last question concerning what is remarked for multiple comparison, approaches to several problems such as abnormality and heteroscedasticity were provided. Philosophy and strategy to multiple comparison problems were discussed.

摘要

在不假定具备统计学专业知识的情况下,讨论了多重比较的问题。对于第一个关于为何使用多重比较程序的问题,简要概述了统计推断和多重比较的理论基础(包括I型错误率和族系错误率)。对于第二个关于如何正确使用多重比较程序的问题,介绍了多重比较程序,并比较了它们的特点。Dunnett检验、Tukey检验和Scheffe检验的比较族各不相同。Dunnett检验、Williams检验和线性回归分析中剂量反应关系的假设也各不相同。Duncan检验不能将族系错误率控制在固定水平。对于最后一个关于多重比较需注意事项的问题,提供了针对诸如异常性和异方差性等几个问题的处理方法。讨论了多重比较问题的理念和策略。

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