Is there a simple rule for interpretation of Interactions (and their directions) in binary logistic

Logistic regression spss interaction. By using our site, you acknowledge that you have read and understand our Cookie Policy, Privacy Policy, and our Terms of Service. Is there a simple rule for interpretation of Interactions (and their directions) in binary logistic regression? [duplicate] This question already has an answer here: I have a binary logistic regression with Y (a disease) and 5 independent variables (and some of their 2-sided interactions which did not cause multicollinearity). All of my single IVs significantly predict Y: A: positive beta for males (males are more likely to get affected) B: a positive beta (older people are more likely to be affected) C (yes/no): a positive beta for smoking (smokers are more likely to be affected) D (continuous): a positive beta (more traumatic patients are more likely to have disease) E (yes/no): a Negative beta for treatment (treated cases were less likely to have diseases). Now 4 interactions are significant and I want to interpret them. I know I should state that in a significant interaction, I should say that the effect of variable A on Y differed for B(1) and B(2). For example the effect of age on disease differed in males and females. But I don't know in which class (males or females), it was greater, and I don't know how to determine it. The significant interactions and their direction of betas are as follows: 4 by 3: positive beta 4 by 5: positive beta 1 by 2: Negative beta 3 by 2: Negative beta.