The data are essentially scores obtained by using the semantic differential
instrument (scores from 17) and the sections represent number of students
(cases). So each student should have a score corresponding to 20 different
items (variables) respectively. Raw data are transferred to SPSS and all
I'm trying to do is to explore the number of factors emerging from the 20
variables. So, from the Scree plot and eigenvalue condition > 1, there are
3 factors extracted. However, it still does not explain why the determinant
of the correlation matrix is 0 and I'm not sure if this data becomes
inadmissible on those grounds, despite having satisfied the minimum criteria
for factor analysis.
Another strange aspect is that the residual matrix does not have values
close to 0 at all. In fact, some of the values are > 0.1 and a lot of the
values are negative. So, has the factor extraction been inefficient or
should some of the variables be removed?
The reliability statistics summary:
Summary Item Statistics
Mean Min. Max. Range Max / Min
Variance N of Items
Item Means 3.630 2.390 5.949 3.559 2.489 .813 20
Item Variances 1.743 1.240 2.338 1.098 1.886 .091
20
InterItem .015 .567 .615 1.182 1.085 .115
20
correlations
The highest square multiple correlation value is .624. None of them has a
SMC of 1.00 with other items.
Thanks for your help!

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