On Jun 22, 6:05 pm, shilin...@yahoo.com wrote: > You should use -2(LL_reduced - LL_full) which is distributed as > chi-square df=# of variables reduced. > The error term in logistic or probit model is not useful. The > distribution of Deviance_reduced - Deviance_full is not known. The > definitions of both terms are different. You should not expect they > would be equal to one another. > > HTH > > On Jun 21, 3:17 pm, Bminer <b_mi...@live.com> wrote: > > > I am used to testing constraints on parameters (two nested models) in > > logistic regression as either: > > > Deviance_reduced - Deviance_full > > or > > -2(LL_reduced - LL_full). Both give the same value to compare to > > critical values of chi-square. > > > Using genmod and a normal error, identity link model the two values > > above are not the same. Why? > > > Which should be used in a likelihood ratio test? > > Thanks!

Hi Thanks for the reply. But, I see many authors saying to subtract deviances or to compute deviance_full - deviance_reduced / scale. Here is an example (look under Analysis of Deviance) http://www.unc.edu/courses/2006spring/ecol/145/001/docs/lectures/lecture22.htm#deviance

Its confusing because if you run a logistic regression with genmod, deviance_full - deviance_reduced is the same exactly as -2(LL_reduced - LL_full). If you run normal error with identity link, they are not.