This paper introduces a modification to the Rule Space diagnostic classification procedure to allow for processing of response vectors that contain missing data. Rule Space is an approach to diagnostic classification that involves characterizing examinees' performances in terms of an underlying cognitive model of generalized problem-solving skills. It has two components: (1) a procedure for determining a comprehensive set of knowledge states, where each state is characterized in terms of a unique subset of mastered skills; and (2) a procedure for classifying examinees into one or another of the specified states. Missing data are expected to be a common problem for this approach because, although the procedure for determining the comprehensive set of knowledge states requires a large pool of items, the procedure for examinee classification can be performed with smaller (less expensive) item subsets. This approach to diagnostic classification is illustrated with data collection in the Survey of Young Adult Literacy, a nationwide survey of literacy skills conducted by the National Assessment of Educational Progress (NAEP). The study has four figures and seven tables. An appendix contains a proof of an aspect of the model. (Contains 18 references.) (Author/SLD)