The use of a strategy for determining the comparable common factors in a set of data are illustrated in this report. Both orthogonal and oblique derived solutions were obtained for each of several different initial factor methods. The results were compared across the various solutions and three types of factors were determined: comparable common factors, comparable specific factors, and non-comparable factors. Factor results used for this illustration are the reanalyses of the data of nine of the Guilford studies as previously reported by one of these authors. The number of comparable common factors for the data in any one of the matrices is always considerable fewer than the number of common factors obtained by Guilford. A few of the CCF's agree rather closely with common factors obtained by Guilford. In many instances two or more of Guilford's common factors coalesce into one comparable common factor. (Author/FL)