So I've perused this site and others, and have a question that I can't seem to find the answer to (possibly because I'm unsure how to even word it).
So I'm coming from an ecological stats background, and have done modeling, stepwise regression, etc, but have an interesting problem right now.
I am working on a project where there is scoring done, and it is basically binomial (either they have a response or they don't), but the scores are weighted differently, so one could be 0 or 9 and the next could be 0 or 4. There is one variable that is discrete, but the rest are in that fashion.
What I want to do is to use the very small sample of responses we have (about 150 out of 40000) to test and validate a model that will tell us what variables are most important.
The hard part is that the weights are going to probably be half stats based, half based on the requirements of the business people in my group. They have set the scores, and have some flexibility, but it wouldn't work for me to tell them that the model is most significant in a certain way if that didn't line up with their business definitions.
What I've done is created a model that was fully binomial, and started with that. However, I want to incorporate their scoring, or at least be able to get to a place where we can add in the scoring element while staying in the middle between completely numbers driven and completely business driven.
My long winded question is this: What is the best way to approach this modelwise? Letting them define weights and then just going from there? Or is there a way where I can really just meet them in the middle?