Is dummy coding required when spacing is meaningful (number of days)?

Question

I apologise if this has been asked before. If so, please point me the right way. However, I have had a look and cannot find an appropriate answer.

I am attempting to fit cumulative logit models using the Ordinal (clm) and VGAM (vglm) R packages. I have continuous and discrete explanatory variables. Both discrete variables are the number of days it rained in a month, so take a single integer value between 0-31. As the distances between each value are equal regardless of level (0|1 = 15|16 = 30|31) are dummy variables required?

If so, I understand some R regression packages automatically dummy code factors, is this the case with the clm and vglm packages?

Finally, how would you recommend selecting the reference variable for these dummy variables?

Answer 1

If you are prepared to assume that scientifically the difference between 1 day and 2 days is the same as between 20 days and 21 days then you could enter this as continuous either as a linear term or something more complicated.

Since it is a continuous variable there is no reference category strictly speaking although the intercept in your model will be estimated for your covariates all having the value zero.