Three types of macro-level variables for program analysis--cultural, economic and demographic--provide a context for evaluation and offer alternative explanations for program success or failure. The problems of causality and availability of data, as well as the usefulness of macro variables in meta evaluation are discussed. (Author/CM)

The various costs of Type I and Type II errors of inference from data are discussed. Six methods for minimizing each error type are presented, which may be employed even after data collection for Type I and which minimizes Type II errors by a study design and analytical means combination. (Author/CM)