Why Factor Analysis Often is the Incorrect Model for Analyzing Bipolar Concepts, and What Model to Use Instead

Abstract

Factor analysis of data that conform to the unfolding model often results in an extra factor. This artificial extra factor is particularly important when data that conform to a bipolar unidimensional unfolding scale are factor analyzed. One bipolar dimension is expected, but two factors are found and often are interpreted as two unrelated dimensions. Although this extra factor phenomenon was pointed out in the early 1960s, it still is not widely recognized. The extra factor phenomenon in the unidimensional case is reviewed here. A numerical illustration is provided, and a number of diagnostics that can be used to determine whether data conform to the unidimensional unfolding model better than to the factor model are discussed. These diagnostics then are applied to an empirical example.