[R] Logistic regression and robust standard errors

[Faradj Koliev]

Dear all, 


I use ”polr” command (library: MASS) to estimate an ordered logistic regression.

My model:   summary( model<- polr(y ~ x1+x2+x3+x4+x1*x2 ,data=mydata, Hess = TRUE))

But how do I get robust clustered standard errors? 

I’’ve tried   coeftest(resA, vcov=vcovHC(resA, cluster=lipton$ID)) and summary(a <- robcov(model,mydata$ID)). Neither works for me. So I wonder what am I doing wrong here? 


All suggestions are welcome – thank you! 
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