Higher-order factor analysis
- Higher-order factor analysis
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.
Literature
* http://eric.ed.gov/ERICDocs/data/ericdocs2sql/content_storage_01/0000019b/80/16/8c/6d.pdf B.T. Gray: Higher-Order Factor Analysis
* [http://cat.inist.fr/?aModele=afficheN&cpsidt=16877522 Hans-Georg Wolff, Katja Preising: Exploring item and higher order factor structure with the schmid-leiman solution : Syntax codes for SPSS and SAS]
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