Hi everyone,
Thank you for the responses. I'm not really sure if the solution you provided actually pertains to what I am looking for.
I think I can explain this problem a bit further:
We have two treatments A and B.
Treatment A removes the organ completely, so the probability of having the disease (site-specific) come back is 0% basically. Treatment B has some chances of the disease come back. However, treatment A is associated with a lot of side effects which includes both physical and psychological problems. On the other hand, Treatment B is not associated with these risk.
Therefore, we asked patients which treatment they would choose if for both treatments A and B, local recurrence is 0%. It's most likely that they would choose treatment B since there is no side effects. This is considered their initial choice. If the patient chose A at 0% recurrence, then their are not likely to accept any possibility of local recurrence and the questions stop. However, for the patients that chose B at the start, we increased the percentage of recurrence until the point where they said they cannot accept this risk and switched to A. This is the threshold that I mentioned in my original e-mail.
Now my task is to determine what predicts this threshold of switching. Therefore, I think for the dependent variable it'll be the threshold percentages of local recurrence where patients switched from B to A. If patient chose A then their threshold will be 0%.
I am quite confused as how I am going to get there. Would the beta distribution still work in the case I described above?
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