Non-response is a potential threat to the accuracy of estimates obtained from sample surveys and can be particularly difficult to avoid in longitudinal studies. The purpose of this report is to investigate non-response in Wave III of Add Health and its influence on study results. Non-response in earlier waves of Add Health has been investigated by the Survey Research Unit at the University of North Carolina. Findings showed that total bias for 13 measures of health and risk behaviors rarely exceed 1% in either Wave I or Wave II, which is small relative to the 20% to 80% prevalence rates for most of these measures. In the following section, we present an overview of the Wave III sampling plan and results of the field work. Next, we characterize the non-response found in the original sampling variables. We then take advantage of the longitudinal design of Add Health to estimate total and relative bias on demographics and a variety of health and risk behaviors reported by both non-responders and responders during their Wave I In-home Interview. We conclude with a discussion of how the bias caused by non-response can be minimized during future waves of data collection.