Rotated component matrix

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Claudia M
Hello, I am doing an exploratory factor analysis with 56 manifest variables using SPSS. However after running it, I don't obtain the rotated component matrix. Any idea about the reasons for this problem? Thanks (...) Read more? Sign up for free

  Jaap de Jonge
Editor, Netherlands
 

Rotated Component Matrix

The rotated component matrix, sometimes referred to as the loadings, is the key output of principal components analysis. It contains estimates of the correlations between each of the variables and the estimated components. In this example:

There are moderate-to-strong correlations between the five sports programs and component 1.
The correlations between the current affairs programs and the first component are very low. Typically, when interpreting a component matrix,. correlations of less than 0.3 or 0.4 are regarded as being trivial. (These correlations are commonly referred to as loadings; the correlations can also be negative and in such an instance correlations of between -0.4 or -0.3 and 0.0 are regarded as being trivially small.)
Thus, the first component seems to measure propensity to watch sports programs.
There are moderate-to-strong correlations between the five current affairs programs and the second component and low correlations between the sports programs and this component. Thus, the second component seems to measure propensity to watch current affairs programs.
Source: displayr Principal Components Analysis.

 

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Rotated component matrix
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