# Results with and without interaction

I'm working on an analysis with another person. First we did a logistic regression with study group and variable X. They were both significant. Then we added the interaction between study group and X only the study group and the interaction were significant. Actually, there are 3 groups and only one of the groups and one of the group*X interactions is significant.

I am having a hard time to convince this person that we should not present the odds ratios for X from the first analysis that do not account for this interaction. This person thinks that we can show the results of the first analysis AND then the second analysis. I think this is misleading and will confuse people.

I am not the best at explaining things (as you can tell), so any help with how to argue my point would be appreciated.

The reason the significance of the effects changes is because there is multicollinearity. The interaction effects are doing a better job of explaining some of the effects that previously were explained by $X$ alone. This could happen, for example, if $X$ Is important for one group but not the others. Without the interaction, we are fitting an average X trend to the groups, which could be significant by virtue of the one group where it is significant. I'm not saying that's exactly what is happening, just that that is one plausible scenario.