The purpose of the present paper was to summarize exploratory second and third-order factor analyses and explain interpretation strategies for the higher-order factors, specifically, Gorsuch’s product matrix, the Schmid and Leiman solution, and Thompson’s orthogonally rotated product matrix solution. Exploratory factor analysis is a multivariate technique to reveal information about latent constructs from the measured variables. When researchers choose an oblique rotation, they believe either their factors are correlated or the best solution will result from an oblique rotation. Whenever primary factors are correlated, extracting higher-order factors from an inter-factor correlation matrix is vitally important to understand data from a different perspective. The SAS syntax is provided along with heuristic datasets to assist interested researchers in exploring the techniques. Advantages of each method are discussed.