I am reading a paper on cost-effective analysis and trying to replicate their results. (paper: https://ascopubs.org/doi/full/10.1200/GO.20.00288)
The probabilistic model in the paper assumes that the transition probabilities and utility weights follow the beta distribution. However, the only values given for the transition probability and utility are the base values. The lower limit and upper limit for the parameters are also given, but they can be solved by just multiplying the base values by 0.8 and 1.2, respectively. Is there any way to compute the shape parameters $\alpha$ and $\beta$ of the beta distribution Beta$(\alpha,\beta)$ using just the base values and the lower and upper limits?
What I have researched so far:
According to this book (https://www.herc.ox.ac.uk/downloads/decision-modelling-for-health-economic-evaluation), if the data are represented by a number of events $r$ observed in a sample $n$, we can set $\alpha=r$ and $\beta=n-r.$ The same is said in the appendix (p. 306) of an article (http://www.med.mcgill.ca/epidemiology/courses/EPIB654/Summer2010/EF/example%20PPI.pdf), but again, the only given value on the paper is the base value.
Going back to the paper, they assumed that there are 1000 patients for the study. Using this and from the research, can I set $n$ to be 1000, and $r$ to be 1000*transition probability? Or should I create a health states distribution and set $n$ and $r$ depending on the treatment cycle I am in?