Methodological study demonstrates superior continuous-time model fitting using ct-gimme across heterogeneous cohorts, indicating improved recovery of dynamic individual networks.
model fitting in continuous-time by pooling information across multiple subjects. Likewise, ct-gimme outperforms group-level model fitting in the presence of within-sample heterogeneity. We conclude with an empirical illustration and highlight limitations of the approach relating to identification of meaningful starting values.
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Park et al. (2024) studied this question.
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