Q: When to use proportional odds model? Suppose we fit a proportional odds model to some data with $Y$ the response variable being ordinal. If we get 0 estimated for all the coefficients (except the intercepts), what does that mean? How would we interpret the model?

A: One possibility is that the scale is wrong - e.g. if one of your independent variables was (say) height of adult humans and you had measured it in millimeters, then the effect of each additional mm of height might be so close to 0 that it gets rounded. 
Another is that you've just got a bad model.
Another is that there is no variation in the variables.
Are they exactly 0 or just really small?
