This article describes a method based on Pratt’s measures and demonstrates its use in exploratory factor analyses. The article discusses the interpretational complexities due to factor correlations and how Pratt’s measures resolve these interpretational problems. Two real data examples demonstrate the calculation of what we call the “D matrix,” of which the elements are Pratt’s measures. Focusing on the rows of the D matrix allows one to compare the importance of the factors to the communality of each observed indicator (horizontal interpretation); whereas a focus on the columns of the D matrix allows one to compare the contribution of the indicators to the common variance extracted by each factor (vertical interpretation). The application showed that the method based on Pratt’s measures is a very simple but useful technique for EFA, in particular, for behavioral and developmental constructs, which are often multidimensional and mutually correlated.
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