Degrees of freedom are the number of H1 parameters minus the number of free parameters in the H0 model. If there are fewer free parameters, the degrees of freedom will be larger.
Gerine L posted on Thursday, October 23, 2014 - 7:04 am
Thank you very much for your response. I thought I understood the basics of degrees of freedom. However, I fail to grasp it here, it seems.
For me, it seems like if I put more restrictions on the data (e.g., confine 2 paths to be the same), that means there is less room, thus fewer degrees of freedom. I.e., if I know path 1, I know path 2, hence path 2 cannot be freely estimated once path 1 is known.