The data are essentially scores obtained by using the semantic differential instrument (scores from 1-7) 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 Inter-Item .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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