Thus, the individual intended outcomes should be identified and the program's success gauged against whether those outcomes are worthwhile and whether they were attained. The measures used to describe the development of program participants should not be accepted at face value. They are not necessarily reliable or valid for specific programs. If not, then a local item analysis and perhaps test recalibration is needed. In lieu of control-comparison group hypothesis testing, we advocate the use of case studies, the computation of effect sizes, and the examination of growth curves.
Case studies can provide rich data to help policy makers and researchers understand interventions.
Effect sizes help gauge the relative contributions of the intervention. Growth curves can help identify trends and control for some error. The effects of the Head Start Program on children's cognitive development. Development of mental abilities. From affect to empirical effect.