How is affective change rated with positive adjectives such as good related to change rated with negative adjectives such as bad? Two nested perfect and imperfect forms of dynamic bipolarity are defined using latent change structural equation models based on tetrads of items. Perfect bipolarity means that latent change scores correlate -1. Meaningful structural equation modeling (SEM) analyses of self-rated affect may require analyzing polychoric correlations, if self-ratings are collected using ordered categories. The models were applied to 6 4-wave datasets from Steyer and Riedl (2004). Results suggest that perfect bipolarity is generally compatible with valence self-ratings, whereas imperfect bipolarity is compatible with tension and energy self-ratings. Methodological and substantive limits of the approach are discussed.