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通过中间数据进行学生t检验、方差分析及方差成分分析的结果。

Resolution of Students t-tests, ANOVA and analysis of variance components from intermediary data.

作者信息

Anders Kallner

机构信息

Department of Clinical Chemistry, Karolinska University Hospital, Stockholm, Sweden.

出版信息

Biochem Med (Zagreb). 2017 Jun 15;27(2):253-258. doi: 10.11613/BM.2017.026.

Abstract

Significance testing in comparisons is based on Student's t-tests for pairs and analysis of variance (ANOVA) for simultaneous comparison of several procedures. Access to the average, standard deviation and number of observations is sufficient for calculating the significance of differences using the Student's tests and the ANOVA. Once an ANOVA has been calculated, analysis of variance components from summary data becomes possible. Simple calculations based on summary data provide inference on significance testing. Examples are given from laboratory management and method comparisons. It is emphasized that the usual criteria of the underlying distribution of the raw data must be fulfilled.

摘要

比较中的显著性检验基于成对数据的学生 t 检验以及用于同时比较多个程序的方差分析(ANOVA)。使用学生 t 检验和 ANOVA 计算差异的显著性时,获取平均值、标准差和观测值数量就足够了。一旦计算出 ANOVA,就可以从汇总数据中分析方差成分。基于汇总数据的简单计算可提供显著性检验的推断。文中给出了实验室管理和方法比较方面的示例。需要强调的是,原始数据的基础分布的通常标准必须得到满足。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1e95/5493167/998cde7d6125/bm-27-253-f1.jpg

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