It was introduced in 1948 by Cyril Burt who referred to it as unadjusted correlation.
[1][2] The congruence coefficient can also be defined as the cosine of the angle between factor axes based on the same set of variables (e.g., tests) obtained for two samples (see Cosine similarity).
For example, with perfect congruence the angle between the factor axes is 0 degrees, and the cosine of 0 is 1.
[2] The congruence coefficient is preferred to Pearson's r as a measure of factor similarity, because the latter may produce misleading results.
The computation of the congruence coefficient is based on the deviations of factor loadings from zero, whereas r is based on the deviations from the mean of the factor loadings.