Given the lack of knowledge about the "true" attributes of objects, convergence across different methods for the same attribute is often the best alternative. This type of validity has been called convergent validity (Campbell & Fiske, 1959). Demonstrating convergent validity is not sufficient, however, because convergence alone does not yet guarantee that the methods measure what they should measure. It only shows that the methods measure the same factors. As previously outlined, some or even all of the common factors two methods share may be diagnosti-cally irrelevant. Therefore, additional validation strategies and validity criteria are important (Cronbach & Meehl, 1955; Messick, 1989). In the present context, discriminant validity is a criterion of special interest (Campbell & Fiske, 1959). If a method predominantly measures what it should, it will not converge with measures for attributes unrelated to the attribute of interest, whereas highly consistent individual differences across several intelligence tests indicate convergent validity, equally consistent individual differences between an intelligence test and a creativity test indicate a lack of discriminant validity for either one or both tests.
The above example shows that demonstrating discriminant validity is more difficult than demonstrating convergent validity. This is true because the divergence of two methods indicates their validity only to the extent that the attributes they measure are truly unrelated (e.g., we can expect divergence between an intelligence test and a creativity test only to the extent that intelligence and creativity are unrelated). Yet how can we know the true relation without valid measures? This problem again points to the importance of theory. If a theory states that intelligent individuals are also more creative (Lubart, 2003), some convergence of intelligence tests and creativity tests must occur and total divergence may raise concerns about the validity of either one or both tests.
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