spss kmo 和bartlett 的球形检验

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为什么spss   kmo  和bartlett  的球形检验  没看到？求解

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关键词：Bartlett Bartle Bart 球形检验 SPSS 检验

look if there are these messages

(1) The correlation matrix is not positive definite

So,  You do not get the KMO measures or Bartlett test, but you do get the PC analysis. This implies that the correlation matrix is positive semidefinite but not positive definite (no negative eigenvalues, but at least one 0 eigenvalue). In this case, the determinant of the matrix is 0, which means that the matrix is singular (cannot be inverted using a standard inverse).
The KMO measures require inversion of the matrix, so they cannot be printed. The Bartlett test statistic is a function of the log of the determinant, so it also cannot be computed, since the log of 0 is undefined. The PC analysis results are nevertheless valid, though you may want to identify the sources of the dependencies and reduce the variables

(2) or you get two messages

>Warning # 11301
>The correlation matrix is not positive definite.

and

>Warning # 11283
>Non-positive eigenvalues have been found and the matrix is not positive
>definite.  This may be due to pairwise deletion of missing values.

You get no KMO measures, no Bartlett test and no PC analysis results. This means that there are negative eigenvalues. If your correlation matrix is computed in FACTOR from raw data without pairwise deletion, this would imply imprecision in our calculation of eigenvalues, since correlation matrices involving Pearson correlations and full data are by definition non-negative definite (have no negative eigenvalues)

mssr 发表于 2013-4-27 15:58
look if there are these messages

(1) The correlation matrix is not positive definite

虽然没有那两个检验，我可以直接做因子分析吗？

091230013man 发表于 2013-4-27 16:08
虽然没有那两个检验，我可以直接做因子分析吗？

真心看不懂英文，能不能换个中文版解释下！

mssr 发表于 2013-4-27 15:58
look if there are these messages

(1) The correlation matrix is not positive definite

the  first  state  is  of  mine, i think. so i could believe the result though  there are no that  two test ?

mssr 发表于 2013-4-27 15:58
look if there are these messages

(1) The correlation matrix is not positive definite

while, i try to reduce two  variables  whose   correlation coefficient  is  no  too high, but the result is the same.so i want to know what i could do  with the data   to  get  the  normal  result.thank you !

If the 1st case is yours case then you can use only some variables to see what happened that is to reduce your variables. If you can take KMO you continue to add variables until KMO is not printed. So you can see what is the variable which causes this trouble.
And yes you can use Principal Components analysis

Hope it helps

Thank  you! I already get the result.But the index is too little,so i need add some index.

高手交流，完全看不懂……

需要在 描述 选项中勾选才有的