Many face-to-face surveys use field staff to create lists of housing units from which samples are selected. However, housing unit listing is vulnerable to errors of undercoverage: Some housing units are missed and have no chance to be selected. Such errors are not routinely measured and documented in survey reports. This study jointly investigates the rate of undercoverage, the correlates of undercoverage, and the bias in survey data due to undercoverage in listed housing unit frames. Working with the National Survey of Family Growth, we estimate an undercoverage rate for traditional listing efforts of 13.6 percent. We find that multiunit status, rural areas, and map difficulties strongly correlate with undercoverage. We find significant bias in estimates of variables such as birth control use, pregnancies, and income. The results have important implications for users of data from surveys based on traditionally listed housing unit frames.