Hi All, I ran a binary logistic of Y on three different numerical variables A,B,C respectively. I am having an issue of separation of variables with all of them, meaning that there are values Ao,Bo, Co for each of A,B,C (different values for each, of course) so that for ## A>Ao, B>Bo, C>Co ## all the responses are successes (I guess this forces the slope to diverge to minus infinity for the slope of the curve to accommodate the abrupt change of 1 to 0). Then I increased the success levels to three: high, medium and low, to use an ordinal regression . But now I have a significant lack of fit, with p -->0 on the Chi-squared test. How does one interpret lack-of-fit issues with a Logistic Regression? I know that a lack of fit in a simple linear means that data is not linear but what does it mean for a Logistic? Does it mean the (log of) the data is not distributed like an S-curve ExpL/(1+ExpL) (##L= \beta_0+ \beta_1 x+......##) ? If so, are there any standard , or any, alternatives (e.g for a distribution for the data). Any ideas?