Hello
I have seen many posts (questions and responses) related to multicollinearity, VIF and interaction. After reading all these threads, I still do not get my answer.
Background: I'm currently using a large survey data set in which I tried to test multicollinearity between two independent variables (both are dummies). My outcome/dependent variable is a dummy variable.

My questions are
(Q1) Can I use Vif for this situation? I saw many posts here and in publications that Vif is used, but most of them are used for the continuous outcome/dependent variables.
I am also aware that the interaction term can also be used to check for collinearity. But, mostly I've seen using "regress" but again, their outcome variables are continuous variables.
(Q2) Currently, I used interaction terms to see if there is any interaction between them.
So, here is my code for interaction. Is the code below correct for checking interaction (outcome var= dummy variable; two independent var checking for collinearity are also dummy variables?

. svy, subpop (if COUTYP4==3): logistic illyr i.new_amdeyr##i. anysuideation2, or

Below is the output.
-----------------------------------------------------------------------------------------

illyr | Odds ratio std. err. t P>|t| [95% conf. interval]
--------------------------+----------------------------------------------------------------
new_amdeyr |
Yes | 2.368648 .1665209 12.27 0.000 2.056722 2.727881
1.anysuideation2 | 4.202448 .3737046 16.14 0.000 3.515055 5.024265

new_amdeyr#anysuideation2 |
Yes#1 | .5716726 .0724573 -4.41 0.000 .4431859 .7374096
|
_cons | .155493 .0033261 -87.01 0.000 .1489538 .1623192
-------------------------------------------------------------------------------------------



(Q2.1) If it is not correct, can anyone suggest the correct code?

(Q3) if it is correct, can the code be used for or checking interaction (outcome var= categorical variable; independent variables checking for collinearity are also dummy variables, categorical and independent var?


Thank you so much.