Maybe msm (Multi-state modelling) is a starting point. You'll find the
manual in the package/doc folder after installation.
HTH
Christian
Dear All,
I am struggling with the conceptual aspects of a problem.
I am sure that someone on this list must be familiar with this.
Let's say that you have some cancer data for your patients.
In particular, every patient may undergo up to [i.e. the cycles may
stop earlier for various reasons] 6 cycles of therapy (hormonal or
chemotherapy) whose durations and starting times are known. There are
plenty of other data available, but let us keep it simple for now.
At the end of the therapy cycles, you know if the patient is dead or
alive (in reality, the final states are more as the patient may be
dead with/without cancer or alive with/without cancer, but again,
let's keep it simple for now).
Of course, you want to develop a policy which maximizes the
probability of the patient to be alive at the end of the cycles of
therapies.
Does anybody know how to tackle this in a Markov decision approach?
There are so many R packages dealing with Markov chains that it is
almost confusing for a beginner.
Any suggestion is welcome.
Many thanks
Lorenzo
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