Pocket guide to Exploratory and Confirmatory Factor Analysis in R
![](https://claudiu.psychlab.eu/post/pocket-guide-efa-cfa-in-r/index.en_files/figure-html/rotation-1.png)
One single common factor
i1 | i2 | i3 | i4 |
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i2 | |||
i3 | |||
i4 |
Two uncorrelated common factors
i1 | i2 | i3 | i4 |
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i1 | |||
i2 | |||
i3 | |||
i4 |
Two correlated common factors
i1 | i2 | i3 | i4 |
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i1 | |||
i2 | |||
i3 | |||
i4 |
In Confirmatory Factor Analysis, relationships among factors may be specified, giving rise to the ability to test higher-order structures. For example, the correlation between specific factors F1 and F2 could be accounted for by a higher-order general factor F.