What I'm about to say is just hypothetical, I know basically nothing about medicine. Suppose that seizures at one point didn't have an influence on the probabil

What I'm about to say is just hypothetical, I know basically nothing about medicine. Suppose that seizures at one point didn't have an influence on the probability of seizures later. Then, that seems to me like it would mean that seizures were a kind of independent point process? Like, suppose there's a model where, depending on a person's genetics, age, and, idk, let's say diet, predicts a given rate of seizures, and also that this rate varies continuously with age. In such a model, I don't think we would tend to see something where a person has no seizures until a certain point in their life, and then subsequently begins to have them at roughly a given rate for some period of time, but it would seem compatible with the "seizures causing seizures" idea. Note: I am not claiming that this is what the data actually shows. I have no idea. But, on the other hand, if there were some other invisible property which can at some random point change from state A to state B, and in state B seizures are more common, but seizures don't influence whether in state A or in state B, I'm not sure you could distinguish that from the "seizures cause more seizures" idea? But, if the causal influence wasn't just "have they ever had a seizure", but instead all seizures had an impact on chance of seizure in the near future, then I think that would have statistical effects? tl;dr: I don't know what I'm talking about, but I suspect you could at least in principle distinguish the two models using some statistical properties.