胡纯严,胡良平.如何正确运用方差分析——正交设计定量资料一元方差分析与SAS实现[J].四川精神卫生杂志,2022,35(3):201-206.Hu Chunyan,Hu Liangping,How to use analysis of variance correctly——an analysis of variance for the univariate quantitative data collected from the orthogonal design[J].SICHUAN MENTAL HEALTH,2022,35(3):201-206
如何正确运用方差分析——正交设计定量资料一元方差分析与SAS实现
How to use analysis of variance correctly——an analysis of variance for the univariate quantitative data collected from the orthogonal design
投稿时间:2022-05-10  
DOI:10.11886/scjsws20220510004
中文关键词:  正交设计  试验点  最优水平组合  方差分析  F分布
英文关键词:Orthogonal design  Experimental point  Optimal level combination  Analysis of variance  F distribution
基金项目:
作者单位邮编
胡纯严 军事科学院研究生院北京 100850 100850
胡良平* 军事科学院研究生院北京 100850
世界中医药学会联合会临床科研统计学专业委员会北京 100029 
100029
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中文摘要:
      本文目的是介绍正交设计及其定量资料的方差分析和SAS实现。从自由度角度来划分,正交设计可分为饱和正交设计与非饱和正交设计两类;从因素的水平数角度来划分,正交设计又可分为同水平正交设计与混合水平正交设计两类;从规范化角度来划分,正交设计还可分为标准正交设计与非标准正交设计两类。对来自标准正交设计的定量资料,可采用常规方法进行方差分析;而对来自非标准正交设计的定量资料,需要对方差分析方法做必要的改进。本文基于3个实例,借助SAS软件实现了无重复试验和有重复试验标准正交设计定量资料方差分析。
英文摘要:
      The purpose of this paper was to introduce the orthogonal design and its quantitative data analysis of variance and the SAS implementation. From the perspective of degrees of freedom, the orthogonal design could be divided into the saturated orthogonal design and the unsaturated orthogonal design. From the perspective of the number of factor levels, the orthogonal design could be divided into the same level orthogonal design and the mixed level orthogonal design. From the perspective of normalization, the orthogonal design could also be divided into the standard orthogonal design and the non-standard orthogonal design. Quantitative data from the standard orthogonal designs could be analyzed by the conventional methods, while quantitative data from the non-standard orthogonal designs needed to be improved. Based on three examples, this paper realized the quantitative data analysis of variance with the standard orthogonal design without repeated experiments and with repeated experiments by means of the SAS software.
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