Interpretation of partial least-squares regression models with VARIMAX rotation

The VARIMAX rotation for factor analysis is used to orthogonally transform the factor subspace, resulting from partial least-square regression (PLSR). If the factors are nearly orthogonal, the transformation may help to interpret the physical meaning of each factor without altering the results of a PLSR model. A case study shows that after the VARIMAX rotation, the loading matrix satisfies “the simple structure criterion” and improves its explanatory ability.