Experimental versus correlational studies.
Most studies in cross-cultural psychology are correlational in nature not properly allowing the researcher to make cause and affect inferences. For example comparisons between cultural groups cannot be called experimental since they contain really correlational information. However, the research reported in the literature often treat observed differences as cause and effect relationships, when a third variable or other factors may be responsible for the results. To use a simple example suppose differences are found between two cultures on the rate and quality of innovation. Judging the results as cause and effect might lead to the conclusion that one culture is better at innovating. However, it may be that essential nutrition in childhood is missing in one culture impairing intellectual development, or perhaps there are climatic or other factors that play a role independent of any overall generalization summarized in “culture”.
Strictly speaking cause and effect conclusions are only justified in experimental studies where control and experimental groups receive equivalent treatments. That is very difficult to achieve in most cross-cultural comparative studies. In discussing the results of correlational studies it is well to remember that these studies are exploratory in nature and don’t directly examine cause and effect. However, correlational studies are useful in exploring relationships and may allow us to develop further hypotheses about the domain of interest. Over time and through replication work we may get to understand more about what it is in the culture that produced the initial correlation. Matsumoto and Yoo (2006) suggested that attributing reasons for cultural differences without specific evidence from experimental work contribute to cultural attribution errors. For example the multiple studies in individualism and collectivism have often been used to draw inferences about specific societies in the Western world and Asia. However, unless these constructs are actually operationalized and measured and found present in the samples surveyed, and unless it can be shown that these constructs are responsible for the observed differences then the attributed difference is not verified.
Date: 2015-01-11; view: 828