In testing gender difference on the relationship between variable A and B,
- A is the covariate (or independent variable)
- B is the dependent variable
- Gender is the factor
As I understand it, if there is a significant interaction between the covariate and factor, then the analysis should be stopped as this violates an assumption of ANCOVA.
My question is: What next?
(I am asking this question because most text books only deal with non-significant interaction, hence there is very little guidance on what to do next if the interaction is significant, as in my case.)
Does the above violation of the assumption mean that I cannot do any further statistical test? (This may be a blessing in disguise for me!)
Can I draw a scatter plot of A and B with different colours for male and females and then discuss the slopes? (This will make intuitive sense to my target audience.)
The goal of my project is to see if the relationship between A and B is affected by gender.
Best Answer
This is not a problem. If you know that you want to see if the A-B relationship differs by sex, do a regression that compares the A-B relationship in different sexes. The interaction is the whole point.
As a by-product, this analysis will tell you what the intercept and slopes are in the different sexes, which you can add to your scatterplot.