A common class of survey designs involves selecting all people within selected households. Generalized regression
estimators can be calculated at either the person or household level. Implementing the estimator at the household level has the convenience of equal estimation weights for people within households. In this article the two approaches are compared theoretically and empirically for the case of simple random sampling of households and selection of all persons in each selected household. We find that the household level approach is theoretically more efficient in large samples and any empirical inefficiency in small samples is limited.