My goal is to assign vehicles a “risk” score (perhaps on a scale of 1 to 5) based on their history. I have data on the vehicle’s age, model, mileage, and dates it was repaired. This risk score would be used to help prioritize vehicles that should be checked for maintenance.
My proposed approach is to apply a Cox proportional hazards model. I haven’t studied survival analysis methods, but it seems like this model would be able to tell me the likelihood of a vehicle surviving at a given time, so it would yield a value between 0 and 1. I was thinking about binning the output, so if the likelihood of survival is between 0.8 and 1, assign the risk 1.
- Is this approach valid? What are some other ways of approaching the problem?
- I’m not really sure how to use the data about the repairaton history (the date(s) the vehicles were repaired). I think it’s a useful variable to include. If a vehicle was repaired recently, then the likelihood of survival should be high.