The website essentially suggests using each variable as a dependent
variable in a separate regression using all other variables as
independent variables, and then using the following command:
display "tolerance = " 1-e(r2) " VIF = " 1/(1-e(r2))
to calculate the Variance inflation factor. However, this only seems to
work if the dependent variable is continous and the regression is OLS.
Is there a way to measure the variance inflation factor for categorical
variables in a complex survey design? Or is there a better way to
approach this problem?
Personally, I see no problem with that. Multicollinearity is a
problem with the right hand side of the model, i.e. the Xs. It
doesn't matter whether Y itself will be analyzed via ols regression,
logistic regression, or whatever. For example, in a non-svy setting,
if y was a dichotomy that you will be analyzing via logistic
regression, it is nonetheless fine to do something like