# Why does changing how I code my dummy variable change significance?

I have data where my dependent variable is a binary choice (Option A or Option B). I have two predictors: time pressure (pressure or no pressure) and alpha score (continuous).

I am examining whether pressure and alpha score interact to affect choice.

When I code time pressure with a dummy variable where pressure = 1 and no pressure = 0, alpha score is a highly significant predictor:

However, when I change how I arbitrarily coded this dummy variable and instead set it so pressure = 0 and no pressure = 1, this changes the significance of alpha score (not to mention some of my coefficients):

And yet, the interaction and the dummy variable are not changing (only changing in sign).

What is causing these changes?

And, in light of this, what is the most appropriate way to write up/interpret these results?

Edit: In your example, the intercept is the log-odds of the response when both variables are at their reference level (or zero if they are coded as numeric). In your first model with no pressure coded as 0, this is 0.37. In the model with pressure coded as 0 it is 1.28, a difference of 0.91 so this the contribution of pressure to the log-odds of the response when the other variable is 0. Now note that this is exactly the main effect of no_pressure in model 1, confirming the above interpretation of the main effect in the presence of an interaction. This analysis can be readily extended to the other main effect and the interaction.