Dear all,

I have run a logistic regression with several predictors: age; gender (coded "1" for women and "0" for men); dimension 1 of phenomenon X; dimension 2 of phenomenon X; gender*dim1; and gender*dim2.

N=267 (n men = 70; n women = 197).

All variables in the regression model were standardized.

When gender is coded as follow: women "1" and men "0", here are the significant predictors:

Dimension 1 (b+); and gender*dim1 (b-).

Then, I just tried to run the regression in another way, in order to fully understand the significant interaction effect. So, I coded men "1" and women "0". Technically, I expected to find same significant predictors (dim1 & dim1*gender) with same b for dim 1 and opposite b for dim1*gender. However, I found the following significant predictors: dim2 (b-) and gender*dim1 (b+). To me, the significant predictor "dim2" is totally unexpected.

Therefore, I performed two other analyses. I have selected only women (filter) and run the logistic regression with the following predictors: age, dim1, and dim2. The significant predictor was dim2 (b-).

Then, I have selected only men and run the same logistic regression and I obtained dim1 (b+) as a significant predictor.

Can someone help me solve this problem?

Many thanks in advance,