Reasonably carry out mean value comparison: MANOVA of the quantitative data collected from the single group design and the paired design
DOI:10.11886/scjsws20230509002
English keywords:Single group design  Paired design  Mean vector  Variance-covariance matrix  Multivariate analysis of variance
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Author NameAffiliationAddress
Hu Chunyan Graduate School, Academy of Military Sciences PLA China lphu927@163.com
Hu Liangping Graduate School, Academy of Military Sciences PLA China 
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      【Abstract】 The purpose of this article was to introduce the basic concepts, calculation methods, two medical examples and SAS implementation related to the multivariate analysis of variance (MANOVA) for quantitative data with the single group design and the paired design. Basic concepts included the single group design and the paired design, mean vector, MANOVA and preconditions, calculation methods involved the general test statistics and Hotellings T2 test statistics, two medical examples were survey data on nutritional status of tuberculosis patients and trial data on the efficacy of huperzine A in the treatment of age-related memory impairment. With the help of SAS software, the univariate and multivariate difference analysis of quantitative data in two medical cases were carried out, and the differences between these two types of analysis approaches were discussed. 【Keywords】 Single group design; Paired design; Mean vector; Variance-covariance matrix; Multivariate analysis of variance 在医学研究中,由于所研究问题的复杂性,研究者不仅要考虑多个影响因素,而且,还要观测多个定量指标的取值,并希望采用多元统计分析方法将多个定量指标同时纳入统计分析中。在多元统计分析中[1-2],最简单的统计分析方法是多元方差分析,它是一元定量资料t检验或方差分析的推广。对于不同的设计类型下收集的多元定量资料,需要采用相应的多元方差分析方法。本文将介绍2种最简单的设计类型(即单组设计和配对设计)下,多元定量资料的实例、多元方差分析的计算方法以及SAS实现。
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