I have a population of 300 cases. It's split in three sub-populations 50, 50 and 200 in size.
I have developed three (different) models resulting in a score variable which rank orders each of the sub-populations separately. The score-ranges for all three segments are different... 40 to 240, 20-410 and 4 to 600. Within each sub-population, higher score means higher level of toxicity i.e. level of risk. Score are not comparable at the moment (that's what I'm trying to achieve).
I know (a priori) that the absolute level of toxicity for first sub population is highest, average for middle sub-population and lowest for the third sub-population.
What I'm trying to achieve is single rating scale. Ideally, I should be rescale each score variables to reflect my a priori knowledge.... first population should have highest scores, then second and then third... something like this
range A from 40 to 240 to 600 to 1000 range B from 20 to 410 to 400 to 700 range C from 4 to 600 to 0 to 500
NOTE: I intentionally allowed for overlaps
Im currently stuck... I know its more art than science, and I will appreciate any ideas you may have.