Many of the advancements reconciling individual- and group-level results have occurred in the context of a discrete-time modeling framework. Discrete-time models are intuitive and offer relatively simple interpretations for the resulting dynamic structures
however, they do not possess the flexibility of models fitted in the continuous-time framework. We introduce ct-gimme, a continuous-time extension of the group iterative multiple model estimation (GIMME
Gates & Molenaar, 2012) procedure which enables researchers to fit complex, high dimensional dynamic networks in continuous-time. Our results indicate that ct-gimme outperforms