Given a will-defined treatment, an expected effect, and an expected cause-effect mechanism, the next step is to design an experiment that will clarify the cause-effect relationship. Developing such a design is complex. The basic aim, however, is straightforward; to introduce deliberate and systematic variations in the strength of the treatment and in the characteristics of those people exposed to it, so that the resulting pattern of behavioral responses permits identification of how the effects vary both as the treatment changes and as the characteristics of those exposed to the treatment change. If the number of treatment variations is numerous in comparison to the number of enrolled families or individuals, the experiment may fail to detect the impact of each of the tested variations with adequate precision. In this case the experiment will have failed in its basic purpose.
For this reason, experiments cannot be designed to test everything. While large-scale social experiments can and do collect a great deal of information on many issues, the most precise data collected will relate to the central issues motivating the experimental design. In the case of SIME/DIME, the experiment was in fact designed to test the effect of two different kinds of social programs on participant work effort. As has been noted, the two policies were a variety of cash transfer or negative income tax programs and several combinations of job counseling and education or training subsidy programs. Many other topics were examined in SIME/DIME — in particular, the relationship between cash transfers and marital stability — but it should be kept in mind that the statistical advantages of the experimentally generated data are somewhat greater for the labor supply analysis.