http://spssx-discussion.165.s1.nabble.com/COvaraince-not-Positive-definite-for-CFA-tp5713427p5713436.html
Complete data: analyzing r or covariances --
If you have the same variable twice, or some other
redundancy (subtotals and total?), the matrix will
have zero as the determinant. Not "negative", but
not positive, either.
So, is the determinant negative? That would indicate
that your correlations are inconsistent, impossible to
be achieved for a set of complete data. You might get
that by analyzing incomplete data with the option of
"pairwise correlations", when the data (and missing)
exist such that that a multiple correlation that would
be near 1.0 for complete data becomes, by formula,
greater than 1.0. (There are also limits shown by the
formulas for partial correlation, but that is less likely
to be relevant for PCA.)
--
Rich Ulrich
> Date: Wed, 30 May 2012 02:27:06 -0700
> From:
[hidden email]> Subject: COvaraince not Positive definite for CFA
> To:
[hidden email]>
> Hello All
>
> Been through all the msgs for this NPD problem Tried the different
> soultions. I have N=200, 14 varaibles for a CFA. They go into 4 LV's.
> Everything seems ok but I get NPD msg. Any suggestions?
...