I have a conceptual question.
I have a dataset with a categorical response variable (integers from 1 till 10) and numerical predictors (independent variables).
I want to be able to predict the value (rank, perhaps) from 1 to 10 depending on the values of predictors.
Logistic regression with a family = binomial will not work because the response variable is not binary.
I can think of several options:
Convert response variable into a factor variable and run a linear regression
keep response variable numeric but round the predictions to the nearest integer using linear regression
Try to use multinom() but not sure if it changes anything relative to the approaches above.
What would you recommend for R?