Nonresponse in surveys may effect representativity, and therefore lead to biased estimates. A first step in exploring a possible lack of representativity is to estimate response probabilities. This paper proposes using the coefficient of variation of the response probabilities as an indicator for the lack of representativity. The usual approach for estimating response probabilities is by fitting a logit model. A drawback of this model is that it requires the values of the explanatory variables of the model to be known for all nonrespondents. This paper shows this condition can be relaxed by computing response probabilities from weights that have been obtained from some weighting adjustment technique.