Calculating mean follow up from ONLY sample size and range I have several observational studies (mostly historical, prior to 1950s) that are looking at relapse rate across several years of follow up period for depression. I only have MINIMUM and MAXIMUM follow up period and sample size (ie one study reports a follow up period of 10-15 years for a sample size of 208 people). However no mean follow up period is provided.
I know from knowledge of the subject/relapse rate trends in modern studies on the same subject that it is a left skewed distribution- ie there will be more relapses in the early period of the study for each individual and then they will become less frequent with time.
So on this basis, ie knowing sample size, range, and type of distribution, is it possible to calculate mean follow up period? Also on STATA, since that is the software i am required to use for this project.
Any help on this would be really appreciated.

You would need to have some idea how relapse times are distributed within the interval.
For example, if they are exponentially distributed, then
the mean of a moderate number of relapse times is roughly 17% of the way from the minimum to the maximum.
Here is a simulation for 200 subjects; results for 100 and were about 19% and results for 500
were about the 15%.
set.seed(2021)
m = 10^5;  v = a = w = numeric(m)
for (i in 1:m) {
 x = rexp(200)
 v[i] = min(x); a[i] = mean(x); w[i] = max(x)
 }
mean(v); mean(a); mean(w)
[1] 0.00499292
[1] 0.9999175
[1] 5.875548
(mean(a)-mean(v))/(mean(w)-mean(v))
[1] 0.1694771

Note: For a uniform relapse distribution, results were about 50%.
