Similarity Judgments and Covariations of Affects: Findings and Implications for Affect Structure Research

Abstract

Results from four studies document very high agreement between the raw data matrices of affect similarity judgments and correlations computed from self-ratings. This was found both for the global structural level, where the correlation-similarity correspondence was as high as the average correspondence of correlation matrices from different studies, and for local subgroups of affects, provided that reliable measures were used. The findings suggest that self-rating correlations and similarity judgments of affects contain essentially the same structural information. As a consequence, the two data types are equally valid starting points for structural analyses of affect, and differences between the models of affect that have been derived from them may reflect primarily method artifacts, such as the use of different scaling methods, rather than differences in the original data. Possible explanations for the high correspondence between self-rating correlations and similarity judgments of affect are discussed.