I have to run a regression predicting the DV (continuous) from an equation with: Y = X1(dichotomous factor, coded 0-1)+X2(dichotomous factor, coded 0-1)+X1X2+M1+M2+M3+...+Mn, where M1...Mn - continuous predictors
My question is: Given that I have two dichotomous variables in the equation, how do I interpret the value of the regression coefficients of the other predictors in the equation? I found different resources suggesting that the other predictors' coefficients should be interpreted as the value of that predictor when all other terms and predictors in the equation are held constant. For me this suggests two things: 1.) They represent the value of M1...Mn when X1=X2=0 or 2.) They represent the value of M1...Mn when X1=X2=mean (?). I'd appreciate it when someone could suggest an interpretation for these terms!