Reviews methods for analyzing outcome data when some data are missing. Presents approach for comparing outcome results in two-group, randomized design with missing data. Proposed analysis is based on concept of "modeling our ignorance" by examining all possible outcomes, given known number of missing results with binary outcome, and then describing distribution of those results. (Author/NB)