 log(1 + income)
   rm(income)
})

m1 &lt;- glm(participation ~ ., family=binomial, data=foodSt)
summary(m1)
rm1 &lt;- glmrob(participation ~ ., family=binomial, data=foodSt)
summary(rm1)
## Now use robust weights.on.x :
rm2 &lt;- glmrob(participation ~ ., family=binomial, data=foodSt,
              weights.on.x = "robCov")
summary(rm2)## aha, now the weights are different:
which( weights(rm2, type="robust") &lt; 0.5)
</code></pre>

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