The goal of the present study was to demonstrate the value of a multiple data analytic approach for testing the cross-cultural generalizability of a personality measure. Data were collected in four different countries (Italy, Germany, Spain, and the United States) on the Big Five Questionnaire (BFQ), which is a measure of the Five Factor Model of personality traits. Different analytical strategies were conducted. Item-level analyses were carried out to study item bias and to select (by means of simultaneous component analysis) the BFQ items that showed better functioning in all countries simultaneously. Scale-level analyses were conducted on item aggregates and were focused on the examination of structural or construct equivalence (i.e., comparability of latent structures). Three analytic approaches were compared (exploratory factor analysis, simultaneous component analysis, and confirmatory factor analysis), and converged in corroborating the basic five factor structure across the four country samples. However, these methods also yielded some noteworthy differences in the conclusions that could be drawn from the analyses. Both the methodological and conceptual implications of this multiple analytic approach are discussed.