Summary. Many health surveys conduct an initial household interview to obtain demographic information and then request permission to obtain detailed information on health outcomes from the respondent's health care providers. A ‘complete response’ results when both the demographic information and the detailed health outcome data are obtained. A ‘partial response’ results when the initial interview is complete but, for one reason or another, the detailed health outcome information is not obtained. If ‘complete responders’ differ from ‘partial responders’ and the proportion of partial responders in the sample is at least moderately large, statistics that use only data from complete responders may be severely biased. We refer to bias that is attributable to these differences as ‘partial non-response’ bias. In health surveys it is customary to adjust survey estimates to account for potential differences by employing adjustment cells and weighting to reduce bias from partial response. Before making these adjustments, it is important to ask whether an adjustment is expected to increase or decrease bias from partial non-response. After making these adjustments, an equally important question is ‘How well does the method of adjustment work to reduce partial non-response bias?’. The paper describes methods for answering these questions. Data from the US National Immunization Survey are used to illustrate the methods.