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

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、两个实例以及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;两个实例分别为“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,对两个实例中的定量资料进行了定量资料对应分析,并对SAS输出结果做出了解释。

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.The basic concepts included variable and sample,explicit variable and latent variable,factor analysis,R-type analysis and Q-type analysis,and correspondence analysis.The 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 quantitative data correspondence analysis,and the SAS output results were given an explanation.