I have a question about splitting the sample versus interacting a variable. My understanding is that if you split the sample and then conduct an analysis you are essentially interacting each independent variable.
I have split my sample based on a a dummy variable. My results are the following:
Model 1 (Split Var=0) Model 2 (Split Var=1) X1 0.614* -0.073 (0.304) (0.487) Constant -2.896* -3.589* (0.820) (1.019)
However, when, I estimate a model with an interaction term the results are the following:
x1 0.614* (0.304) Split Var -0.714 (1.273) X1* Split Var -0.682 (0.574) Constant -2.896* (0.820)
I am surprised by two things. 1) the interaction variable is insignificant. If in the split sample the x1 variable is significant, shouldn't the interaction variable be significant? 2) the coefficient for the main effect (x1) is identical to the coefficient in model 1 for variable x1.
How would you interpret the results? Is this not a conditional relationship? Does the effect of x1 not vary by the split var?