Primary Source: Patton, C. V, and Sawicki, D. S. (1993) Basic Methods of Policy Analysis, Second Edition. Prentice Hall: Englwood Cliffs, NJ.
Quasi-experimental designs are useful for real-world evaluations when a true experiment cannot be conducted – when we cannot randomly assign persons to treatment or control groups, when we cannot control the administration of the program or policy or restrict the policy to a treatment group or when programs are not directed at individuals. The term quasi-experimental unfortunately implies to some persons that there is something wrong or second-rate about the design. Quite to the contrary, quasi-experimental approaches seek to maintain the logic of full experimentation but without the procedures, hardware, techniques, or control of the laboratory. Cook and Campbell’s Quasi-Experimentation provides extensive coverage of this approach and the design options available, including a description of appropriate statistical tests for the designs. There are two basic designs that planners and analysts should find very useful: the non-equivalent control group and the interrupted time-series designs. The non-equivalent control-group design involves the comparison of a treatment group and a similar (but not randomly selected) group before and after the policy or program is implemented. The interrupted time-series design involves the comparison of a treatment group several times both before and after the policy or program is implemented.
Nonequivalent Control-Group Design
The non-equivalent control-group design (Table 1) is read with the Ts and Cs indicating observations or measurements for the treatment and control groups, respectively, and the subscripts 1 and 2 indicating, respectively, preprogram and postprogram measurements. The dashed line indicates that the control group is logically selected so as to be similar, but not necessarily equivalent, to the treatment group. In short, a group, locale, or other entity [...]