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CHAPTER 6: Independent Groups Designs 217from the experimental puzzle. A less preferred, but still possible, alternativefor matching is to use a task that is from a different class than the experimentaltask. For our problem-solving experiment, participants could be matchedon some test of general ability, such as a test of spatial ability. When usingthese alternatives, however, researchers must confirm that performance on thematching task correlates with the performance on the task that is used as the dependentvariable. In general, as the correlation between the matching task andthe dependent variable decreases, the advantage of the matched groups design,relative to the random groups design, also decreases.Even when a good matching task is available, matching is not sufficient toform comparable groups in an experiment. For example, consider a matchedgroups design to compare two different methods of caring for premature infantsso as to increase their body weight. Six pairs of premature infants could bematched on their initial body weight. There remain, however, potentially relevantcharacteristics of the participants beyond those measured by the matchingtask. For example, the two groups of premature infants may not be comparablein their general health or in their degree of parental attachment. It is important,therefore, to use random assignment in the matched groups design to tryto balance other potential factors beyond the matching task. Specifically, aftermatching the infants on body weight, individuals in each pair would be randomlyassigned to one of the two treatment groups. In conclusion, the matchedgroups design is a better alternative than the random groups design when a good matchingtask is available and when only a small number of subjects is available for an experimentthat requires separate groups for each condition.NATURAL GROUPS DESIGN• Individual differences variables (or subject variables) are selected ratherthan manipulated to form natural groups designs.• The natural groups design represents a type of correlational research inwhich researchers look for covariations between natural groups variablesand dependent variables.• Causal inferences cannot be made regarding the effects of natural groupsvariables because plausible alternative explanations for group differencesexist.Key ConceptResearchers in many areas of psychology are interested in independent variablesthat are called individual differences variables, or subject variables. Anindividual differences variable is a characteristic or trait that varies across individuals.Religious affiliation is an example of an individual differences variable.Researchers can’t manipulate this variable by randomly assigning peopleto Catholic, Jewish, Muslim, Protestant, or other groups. Instead, researchers“control” the religious affiliation variable by systematically selecting individualswho naturally belong to these groups. Individual differences variables suchas gender, introversion–extraversion, race, or age are important independentvariables in many areas of psychology.