Factor Analysis: Rotated Matrix

When conducting an exploratory factor analysis (EFA) or principal components analysis, researchers often perform a procedure to rotate the factor matrix. In communication research, it is relatively rare that a researcher would conduct a factor analysis without rotation. Rotation of the factor structure entails moving the factor axes in order to provide a new perspective on patterns in the underlying factor structure. Factor rotation provides many benefits. An unrotated factor solution simply tries to explain the maximum amount of variance with a minimal number of factors; however, most communication researchers use factor analysis in order to extract meaningful data that accurately represents the underlying nature of their data. Rotating the factor structure allows for the extraction of factors with face validity—the goal is to derive ...