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| 合理进行多元分析——定量资料对应分析 |
| Reasonably carry out multivariate analysis：Quantitative data correspondence analysis |
| 投稿时间：2023-08-14 修订日期：2023-08-14 |
| DOI：10.11886/scjsws20230814001 |
| 中文关键词: 对应分析 因子分析 变量变换 协方差矩阵 特征值 |
| 英文关键词:Correspondence analysis Factor analysis Variable transformation Covariance matrix Eigenvalue |
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| 中文摘要: |
| 本文目的是介绍与定量资料对应分析有关的基本概念、计算方法、2个实例及SAS实现。基本概念包括变量与样品、显变量与隐变量、因子分析、R型分析与Q型分析、对应分析；计算方法涉及基本原理、变量变换、构建R型和Q型协方差矩阵、因子分析；2个实例中的资料分别为“某年中国10个省份农村居民家庭人均消费支出数据”和“不同民族的各种基因出现的频率”；借助SAS软件,对2个实例中的定量资料进行了定量资料对应分析,对SAS输出结果做出了合理的解释。 |
| 英文摘要: |
| The purpose of this article was to introduce the basic concepts, calculation methods, two examples and SAS implementation related to the quantitative data correspondence analysis(QDCA). The basic concepts included variable and sample, explicit variable and latent variable, factor analysis, R-type analysis and Q-type analysis, and correspondence analysis; calculation methods involved the basic principles, variable transformation, construction of R-type and Q-type covariance matrices, and factor analysis; the data in the two examples were "per capita consumption expenditure data of rural households in 10 provinces in China in a certain year" and "frequency of occurrence of various genes of different ethnic groups"; with the help of SAS software, the quantitative data in the two examples were analyzed by QDCA, and the SAS output results were given a reasonable explanation. |
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