Rotation Methods

Rotation methods are techniques used in factor analysis to make the results more interpretable. After extracting factors, the initial solution might be complex or hard to understand. Rotation adjusts the factors by shifting their axes, aiming to clarify the structure by grouping related variables more clearly. There are two main types: orthogonal rotations, which keep factors at right angles (unchanged relationships), and oblique rotations, which allow factors to correlate. These methods help reveal more meaningful patterns in data, making it easier to identify underlying dimensions or constructs.