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Pocket guide to Exploratory and Confirmatory Factor Analysis in R

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  • One single common factor

    i1 i2 i3 i4
    i1 1.00 0.64 0.64 0.64
    i2 0.64 1.00 0.64 0.64
    i3 0.64 0.64 1.00 0.64
    i4 0.64 0.64 0.64 1.00

    Two uncorrelated common factors

    i1 i2 i3 i4
    i1 1.00 0.64 0.00 0.00
    i2 0.64 1.00 0.00 0.00
    i3 0.00 0.00 1.00 0.64
    i4 0.00 0.00 0.64 1.00

    Two correlated common factors

    i1 i2 i3 i4
    i1 1.00 0.64 0.41 0.41
    i2 0.64 1.00 0.41 0.41
    i3 0.41 0.41 1.00 0.64
    i4 0.41 0.41 0.64 1.00

    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.

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