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Using the library for disease progression #2
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Hi |
Hi Thank you for your response. Well, I don’t the DAG of my problem, but I can briefly summarise it as follows:
There is one continuous variable that I want to model, the disability level. We can say that this variable goes from 0 (no disability) to 1 (death). The probabilities to move from one state to another may be assigned randomly. My main doubt here is that the disability level must tend to increase along the time disregarding the state and I don’t know how to model this kind of dependence. Also, bear in mind that it is quite difficult to define a CDF for the continuos variable for each state, because the disability level increases along time. Consequently, the disability level could have a CDF for early relapses, and another completely CDF for later relapses. I'm new in bayesian network analysis, I don't know if it is possible to create a DAG that models such a progression of MS, and thus allow me to create synthetic time series that represent the disability progression. I would be more than happy to have a toy sample that could approximate this kind of problem. I would appreciate you help, Thanks in advance |
Hi
I'm very interested in using this library for generating time series that represent some disease progression. In particular, I'm working on diseases where disability levels in the persons commonly increase along time, like in Parkinson or Multiple Sclerosis.
How can I use this library to obtain time series where a disability-level (continuous variable) increases over time?
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