| Hu Chunyan,Hu Liangping,Reasonably carry out multivariate analysis： quantitative data correspondence analysis[J].SICHUAN MENTAL HEALTH,2023,36(S1):73-78 |
| Reasonably carry out multivariate analysis： quantitative data correspondence analysis |
DOI：10.11886/scjsws20230726001 |
| English keywords:Correspondence analysis Factor analysis Variable transformation Covariance matrix Eigenvalue |
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| English abstract: |
| 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. |
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