- Thread starter firefly
- Start date

Thank you for your response. From what you say, I infer that if two variables correlate with one another then they will interact? I have not come across this in my statistical studies. If two variables are highly correlated I am inclined to consider removing one from the analysis rather than try to model an interaction between them.

But I know that interactions are possible between variables that are not correlated; how would I detect interaction effects between such variables?

But I know that interactions are possible between variables that are not correlated; how would I detect interaction effects between such variables?

Two points here.

1) Does correlation imply interactions? your responses so far seem to imply so, but I have never heard of this before.

2) Yes, VIF has a lot to do with collinearity, but how is it related to interaction effects, especially when the variables are not correlated as mentioned in your quote from my previous mail

2) Multicollinearity is interaction between IVs. Typically a VIF value greater than 10 MAY suggest multicollinearity.