I have a small sample of 96 observations. I developed an empirical model with 4 independent variables to explain the independent variables and the results make sense. A referee asked me to add additional 9 variables to the model to test the robustness of the model. The results no longer make sense including 2 dependent variables of the 4 initial variables. I don't have any multicollinearity issue and I doubt that it s because the sample is small and the number of variables is 13 (too much for the small sample) . does it make sense? in general what is the maximum number of dependent variables that would result a reliable results for such a sample?