Attrition from conditions in randomized experiments is common. Yet it is difficult to assess the possible effects of attrition because the outcome status of the dropouts is usually unknown. This article develops methods to assess those effects in studies with dichotomous outcomes, illustrating the methods with randomized experiments in drug abuse treatment, smoking cessation treatment, and alcoholism treatment. The methods include computing the lowest and highest possible effect sizes that could have been observed, enumerating the percent of possible study outcomes below a given threshold, estimating the probability that an outcome beyond any given threshold would be observed if all participants were measured, and constructing attrition analysis plots showing the effects of attrition under varied assumptions. For the kind of study to which they apply, these methods should replace the treatment of missing participants as failures in an “intent-to-treat” analysis. A user-friendly personal computer program is available to implement all of these analyses.