The basis for unbiased inference from relatively small observed samples to largely unobserved populations is probability sampling. Such samples, in turn, provide the foundation for studies that inform national, regional, and local economic, social, and health policies, as well as marketing and political decisions (e.g., National Research Council 2006). Underlying this inferential process, however, is the assumption that all elements designated for the sample are actually observed or measured. In recent years, increasing violation of this assumption because of an inability to contact sample members or because of their unwillingness to participate has led to increasing attention to survey nonresponse. "Nonrespondents" are those missing from a probability sample; the largest components of nonresponse, and therefore those of greatest concern to survey methodologists, are noncontact and refusal. These components have different causes and may, therefore, have different consequences for survey estimates (Groves and Couper 1998; Groves, this issue).