The circumplex model of affect has been among the most widely studied repre
sentations of affect. Despite the considerable evidence cited in support of
it, methods typically used to evaluate the model have substantial limitati
ons. In this article, the authors attempt to correct past limitations by us
ing a covariance structure model specifically designed to assess circumplex
structure. This model was fit to 47 individual correlation matrices from p
ublished data sets. Analyses revealed that model fit was typically acceptab
le and that opposing affective states usually demonstrated strong negative
corralations with one another. However, analyses also indicated substantial
variability in both model fit and correlations among opposing affective st
ates and suggested several characteristics of studies that partially accoun
ted for this variability. Detailed examination of the locations of affectiv
e states for 10 of the correlation matrices with relatively optimal charact
eristics provided mixed support for the model.