I have a quite large data set (approximately 1500 individuals, with very few missing values). My goal would be to predict age (thus, a positive, continuous outcome) using approximately 10 ordinal variables representing biological/developmental indicators. Each ordinal variable has exactly 8 stages. What method would be best suited for such a question?
- I think there are few methods that natively handle ordinal variables. So, should I treat the ordinal predictors as numerical, or as nominal?
- Is there some way of using simply a linear regression here? (Maybe in combination with some penalization method?)
- Ideally, I would like to get not only a point estimate of age, but also a prediction interval.
I've already tried random forests, which perform quite correctly, but I wonder about possibly better alternatives in this use case.