Comment by mellavora

Isn't Molenaar looking at networks of symptoms over time? Yes, in any multi-variate time series, when one is searching for relationships between the variables (and allowing that you may have multiple sets of time series which may have some type of grouping, i.e. observations from a set of people with one diagnosis vs observations from a set of people with a contrary or with no diagnosis), then yes, any attempt to find co-relations in the multivariate signal need to account for the underlying statistical distribution of the signal components. The normal distribution isn't a bad first a priori approximation, but you really need to check.

side note- it also isn't clear that you can group by diagnosis, see, for example, https://pubmed.ncbi.nlm.nih.gov/29154565/, which shows that even within diagnostic groups there is substantial individual variation.