A cluster sampling model, which is essentially a model for random effects, is analysed using the concept of balanced sampling. It is found that this method of sampling leads to formulae which specify the sampling effort amongst chosen clusters, and which yields the expansion estimator as optimal. Some extensions and generalisations are indicated.