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**Statistical rotation** may be viewed as a form of **Higher-order factor analysis** is a statistical method consisting of repeating steps factor analysis – oblique rotation – factor analysis of rotated factors... Its merit is to enable the researcher to see the hierachical structure of studied phenomena.

To interpret the results, one proceeds either by post-multiplying the primary factor pattern matrix by the higher-order factor pattern matrices (Gorsuch, 1983) and perhaps applying a Varimax rotation to the result (Thompson, 1990) or by using a Schmid-Leiman solution (SLS, Schmid & Leiman, 1957, also known as Schmid-Leiman transformation) which attributes the variation from the primary factors to the second-order factors.