Nonparametric regression is the model-based sampler's method of choice when there is serious doubt about the suitability of a linear or other simple parametric model for the survey data at hand. It supersedes the need for use of design weights and standard design-based weights. Recognition of this is especially helpful in confronting problems in sampling situations where design weights are missing or questionable. One example is the case where we have data from two (or more) samples from a given population. We discuss this case.