Dear List,

randomise offers the -D option, i.e. it demeans the input data before model fitting.
Alternatively, one has to model the mean as a regressor.

As I understand, this regressor - as any linearly independent regressor - would cost 1 degree of freedom.
I was wondering, whether this 1 degree of freedom is considered by randomise when omitting the mean regressor and using the -D option instead. (could not find the answer in the docs).

THX + kind regards,
andi