There are several reasons why a determinant can be zero.
In the earlier post, where the N was less than the number
of variables, that was sufficient reason -- the determinant
is zero if the matrix is not "full-rank", since the N is a
maximum of the rank of a covariance matrix. Rank could be less.
Also, a matrix is not full rank if any variable is a "constant":
that is, zero for some standard deviation.
A matrix is not full rank if any variable is a linear
combination of the other variables.... This happens when
a variable happens to be entered twice, or when the list
of variables includes a set subscores and their total.
>
> I am facing the same problem.
>
> I already tried to use Guttman and Split Half, but this statement "The
> determinant of the covariance matrix is zero or approximately zero.
> Statistics based on its inverse matrix cannot be computed and they are
> displayed as system missing values." still there.
>
> I have analyzed 73 respondents with 23 variables.
>
> If possible, I do appreciate any advices from anyone.
>
> Can I still use Cronbach's Alpha to state that my survey was reliable?
It still does show the internal reliability, yes.
--
Rich Ulrich
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