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The prevalent method to analyze data from several groups of individuals is to define some ad hoc boundaries of individuals-for example geographic, ethnic or gender boundaries and then compare statistical means and deviations between groups. This method assumes homogeneity within each ad hoc group and treats differences among individuals in each group as subgroup variations. Instead of imposing ad-hoc boundaries, we used a new method "heterogram analysis" (Maruyama, 1999) that looks for response datagenerated grouping of individuals and the meaningfulness of each emerging group. This approach was applied to individual-level individualism-collectivism data from three countries. The results showed five individual types that cut across traditional geographic, ethnic and gender boundaries. These types were validated by two other measures. Implications of findings are discussed.
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