I have read the previous discussions on interaction effects and main effects, and I have a question on the subject.
I am running a destination choice model (multinomial logit), and I have one continuous variable (distance in meters) and several dummy variables accounting for given behavior (main activity at destination) which I am hypothesizing as having an interaction effect.
In this particular model, the effect of Distance is as expected significant by itself, and also are significant the interactions between Distance and the dummy variables, however, when I try to include the dummy variables alone to get their main effects, the model cannot be estimated even after including only one dummy variable. I illustrate this below:
- Distance+Distance*Dummy2+Distance*Dummy3 = Significant main and interaction effects (s.e. of interaction not estimated)
- Distance*Dummy2+Distance*Dummy3 = Significant interaction effects
- Distance+Dummy1+Dummy2 = Model cant be estimated
- Distance+Dummy1+Dummy2+Distance*Dummy2+Distance*Dummy3 = Model cant be estimated
So my question would be:
1. if it is possible to account only for the interaction terms without the main effects given what I explained before?