I work at an R1 university and am trying to synthesize a dataset that has information about grants that faculty here have won. I want a quick-and-dirty index that balances two things: how much a given faculty member has won in grants in total, and how many grants they have won. Basically, I want a systematic way to identify people who 'win grants', where both the total awarded amounts, and the number of awards, matter.
So the index would (roughly, if not perfectly) adhere to constraints like these:
- if two faculty have roughly same total awarded amounts, but one has a higher number of awards, rank the latter higher
- if two faculty have roughly the same number of awards, but one has a higher total awarded amount, rank the latter higher
Ideally, the index would be mathematical (I could maybe do a simple linear model, but I'm not sure how the calibrate the parameters). It doesn't have to be bulletproof; it's just for identifying potential grant writing mentors.
Any ideas?
Thank you so much!
EDIT: as soon as I posted, I realized the simplest thing to do is just multiply the values together, so index_i = total_i * count_i. This is pretty crude, but I'd be curious how generally useful that index is...
