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Multitrait-multimethod assessment of giftedness: An application of the correlated traits-correlated(methods – 1) model
Structural Equation Modeling: A Multidisciplinary Journal
  • Christian Geiser, Utah State University
  • Samuel D. Mandelman, Columbia University
  • Mei Tan, Columbia University
  • Elena L. Grigorenko, Yale University
Document Type
Taylor & Francis
Publication Date

Although the use of multiple criteria and informants is one of the most universally agreed on practices in the identification of gifted children, few studies to date have examined the convergent validity of multiple informants and objective ability tests in gifted identification. In this study, we illustrate the use of the correlated traits–correlated (methods – 1) or CT–C(M – 1) model (Eid, Lischetzke, Nussbeck, & Trierweiler, 2003) to examine the convergent validity of self, parent, and teacher ratings relative to objective cognitive ability tests in a sample of 145 4th to 6th graders. The CT–C(M – 1) analyses revealed that teacher ratings showed the highest convergence with the objective assessments, whereas self-ratings had the lowest reliabilities and insufficient validity. Parent ratings were more reliable and valid than self-reports, but were outperformed by teacher ratings for most abilities. Overall, the CT–C(M – 1) analyses showed that the convergent validity of the ratings relative to the objective test battery was highest for numerical and lowest for creative abilities. Furthermore, whereas part of the shared variance between parent and teacher ratings reflected true convergent validity, agreement between parent and self-reports was entirely due to a shared rater variance. Our analyses demonstrate the usefulness and proper interpretation of the CT–C(M – 1) approach for examining convergent validity and method effects in multitrait–multimethod data.

Citation Information
Christian Geiser, Samuel D. Mandelman, Mei Tan and Elena L. Grigorenko. "Multitrait-multimethod assessment of giftedness: An application of the correlated traits-correlated(methods – 1) model" Structural Equation Modeling: A Multidisciplinary Journal Vol. 23 Iss. 1 (2015) p. 76 - 90
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