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| 合理进行多元分析——度量型多维尺度分析 |
| Reasonably carry out multivariate analysis： metric multidimensional scaling analysis |
| 投稿时间：2023-08-14 修订日期：2023-08-14 |
| DOI：10.11886/scjsws20230814003 |
| 中文关键词: 度量型 多维尺度 距离矩阵 相似系数矩阵 拟合构图 |
| 英文关键词:Metric multidimensional scale Distance matrix Similarity coefficient matrix Configuration |
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| 中文摘要: |
| 本文目的是介绍与度量型多维尺度分析有关的基本概念、计算方法、2个实例及SAS实现。基本概念包括度量型与多维尺度、应用场合、距离矩阵与相似系数矩阵、研究对象、拟合构图与构图、多维尺度分析的基本思想；计算方法涉及经典多维尺度分析和最小平方多维尺度分析；2个实例中的资料分别是“甘肃省12个主要城市间的距离”与“8个测试项目之间的相关系数矩阵”；借助SAS软件，对2个实例中的资料分别进行了多维尺度分析，对SAS输出结果做出了合理的解释。 |
| 英文摘要: |
| The purpose of the paper was to introduce the basic concepts, calculation methods, two examples and SAS implementation related to the metric multidimensional scaling analysis. Basic concepts included metric and multidimensional scaling, application occasions, distance matrix and similarity coefficient matrix, research objects, configuration and composition, basic ideas of multidimensional scaling analysis; the calculation method involved classical multidimensional scaling analysis and least square multidimensional scaling analysis; the data in the two examples were "distance between 12 major cities in Gansu Province" and "correlation coefficient matrix between 8 test items"; with the help of SAS software, the multidimensional scale analysis was carried out on the data in the two examples, and a reasonable explanation was given for the output results of SAS. |
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