Coordination is a taxonomy of how processes change together through time. It depicts the changes of 2 or more variables in terms of the strength and consistency of their covariation, the directionality of their covariation (i.e., do increases in 1 variable correspond with increases [in-phase] or decreases [anti-phase] in the other variable), and the timing of their covariation (i.e., do both variables change at the same rate or does 1 variable change faster than the other). Current methods are able to characterize some, but not all, of these aspects of coordination and provide incomplete information as a result. This study addresses this limitation by demonstrating that multivariate Latent Change Score models can be used to fully differentiate all possible coordination patterns. Furthermore, one can then expand coordination beyond the 2-outcome case to test arrangements of underlying coordination mechanisms or patterns. Examples using 2 simultaneous Latent Change Score models and 4 simultaneous Latent Change Score models illustrate this approach within the context of adolescents and parents regulating Type 1 diabetes.