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CHAPTER 6: Independent Groups Designs 215of college students will generalize to groups of older adults, working professionals,less educated individuals, and so forth? Underwood and Shaughnessy(1975) suggest one possible approach worth considering. Their notion is that weshould assume that behavior is relatively continuous across time, subjects, andsettings unless we have reason to assume otherwise. Ultimately, the externalvalidity of research findings is likely to be established more by the good judgmentof the scientific community than by definitive empirical evidence.MATCHED GROUPS DESIGN• A matched groups design may be used to create comparable groupswhen there are too few subjects available for random assignment to workeffectively.• Matching subjects on the dependent variable task is the best approach forcreating matched groups, but performance on any matching task mustcorrelate with the dependent variable task.• After subjects are matched on the matching task, they should then berandomly assigned to the conditions of the independent variable.Key ConceptTo work effectively, the random groups design requires samples of sufficientsize to ensure that individual differences among subjects will be balancedthrough random assignment. That is, the assumption of the random groupsdesign is that individual differences “average out” across groups. But howmany subjects are required for this averaging process to work as it should? Theanswer is “It depends.” More subjects will be needed to average out individualdifferences when samples are drawn from a heterogeneous population thanfrom a homogeneous one.We can be relatively confident that random assignment will not be effectivein balancing the differences among subjects when small numbers of subjectsare tested from heterogeneous populations. However, this is exactly the situationresearchers face in several areas of psychology. For example, some developmentalpsychologists study newborn infants; others study the elderly. Bothnewborns and the elderly certainly represent diverse populations, and developmentalpsychologists often have available only limited numbers of participants.One alternative that researchers have in this situation is to administer allthe conditions of the experiment to all the subjects, using a repeated measuresdesign (to be discussed in Chapter 7). Nevertheless, some independent variablesrequire separate groups of subjects for each level. For instance, suppose researcherswish to compare two types of postnatal care for premature infants andit is not possible to give both types of care to each infant. In this situation, andmany others, researchers will need to test separate groups in the experiment.The matched groups design is a good alternative when neither the randomgroups design nor the repeated measures design can be used effectively. Thelogic of the matched groups design is simple and compelling. Instead of trustingrandom assignment to form comparable groups, the researcher makes thegroups equivalent by matching subjects. Once comparable groups have beenformed based on the matching, the logic of the matched groups design is the