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322 PART IV: Applied ResearchQuasi-experiments are recommended when true experiments are not feasible.Some knowledge about the effectiveness of a treatment is more desirablethan none. The list of possible threats to internal validity that we reviewedearlier can be used as a checklist in deciding just how good that knowledge is.Moreover, the investigator must be prepared to look for additional kinds of evidencethat might rule out a threat to internal validity that is not specifically controlledin a quasi-experiment. For example, suppose that a quasi-experimentdoes not control for history threats that would be eliminated by a true experiment.The investigator may be able to show that the history threat is implausiblebased on a logical analysis of the situation or based on evidence providedby a supplementary analysis. If the investigator can show that the history threatis implausible, then a stronger argument can be made for the internal validity ofthe quasi-experiment. Researchers must recognize the specific shortcomings ofquasi-experimental procedures, and they must work like detectives to providewhatever evidence they can to overcome these shortcomings. As we begin toconsider the appropriate uses of quasi-experiments, we need to acknowledgethat there is a great difference between the power of the true experiment andthat of the quasi-experiment. Before facing the problems of interpretation that resultfrom quasi-experimental procedures, the researcher should make every effort possible toapproximate the conditions of a true experiment.Perhaps the most serious limitation researchers face in doing experiments innatural settings is that they are frequently unable to assign participants randomlyto conditions. This occurs, for instance, when an intact group is singled out fortreatment and when administrative decisions or practical considerations preventrandomly assigning participants. For example, children in one classroom or schooland workers at a particular plant represent intact groups that might receive a treatmentor intervention without the possibility of randomly assigning individuals toconditions. If we assume that behavior of a group is measured both before andafter treatment, such an “experiment” can be described as follows:O 1 X O 2where O 1 refers to the first observation of a group, or pretest, X indicates a treatment,and O 2 refers to the second observation, or posttest.This one-group pretest-posttest design represents a pre-experimental designor, more simply, may be called a bad experiment. Any obtained difference betweenthe pretest and posttest scores could be due to the treatment or to any ofseveral threats to internal validity, including history, maturation, testing, andinstrumentation threats (as well as experimenter expectancy effects and noveltyeffects). The results of a bad experiment are inconclusive with respect tothe effectiveness of a treatment. Fortunately, there are quasi-experiments thatimprove upon this pre-experimental design.The Nonequivalent Control Group Design• In the nonequivalent control group design, a treatment group and acomparison group are compared using pretest and posttest measures.