怎样看SPSS主成分分析的component matrix 表

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在做主成分分析时，是把SPSS－DATA　REDUCTION－FACTOR输出结果中的component matrix每一列的主成分看作表中最左边一列原变量的函数，还是把最左边一列原变量看作是主成分的函数。

[此贴子已经被作者于2006-4-17 14:32:13编辑过]

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关键词：Component SPSS主成分分析 matrix 主成分分析 SPSS SPSS 主成分分析 matrix Component 主成分分析法 spss主成分分析 逐步回归分析 多元回归分析 因子分析法 应用时间序列分析

Component Matrix - This table contains component loadings, which are the correlations between the variable and the component. Because these are correlations, possible values range from -1 to +1. On the /format subcommand, we used the option blank, which tells SPSS not to print any of the correlations that are .3 or less. This makes the output easier to read by removing the clutter of low correlations that are probably not meaningful anyway.

Component - The columns under this heading are the principal components that have been extracted. You usually do not try to interpret the components the way that you would factors that have been extracted from a factor analysis. Rather, most people are interested in the component scores, which are used for data reduction (as opposed to factor analysis where you are looking for underlying latent continua). You can save the component scores to your data set for use in other analyses using the /save subcommand.

http://www.ats.ucla.edu/stat/SPSS/output/principal_components.htm

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component matrix每一列的主成分看作表中最左边一列原变量的函数

成分矩阵中 主成分法是用原变量的表达式表示每一列即每个主成分， 因子分析法是用各因子的表达式表示每一个原变量，反映各因子在各变量上的载荷，因子分析中的公因子表达式算得分用的是成分得分矩阵。