Intelligence Research Today is a free monthly online journal that collates and summarizes the latest research about Intelligence, including details on iq, testing, nature vs nurture, cognition. | ||||||||
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Clinical validation of the General Ability Index--Estimate (GAI-E): estimating premorbid GAI.Schoenberg MR, Lange RT, Iverson GL, Chelune GJ, Scott JG, Adams RL Department of Neurology, University Hospitals of Cleveland and Case Western Reserve University School of Medicine, Cleveland, OH 44106-5000, USA. Michael.Schoenberg@uhhs.com The clinical utility of the General Ability Index--Estimate (GAI-E; Lange, Schoenberg, Chelune, Scott, & Adams, 2005) for estimating premorbid GAI scores was investigated using the WAIS-III standardization clinical trials sample (The Psychological Corporation, 1997). The GAI-E algorithms combine Vocabulary, Information, Matrix Reasoning, and Picture Completion subtest raw scores with demographic variables to predict GAI. Ten GAI-E algorithms were developed combining demographic variables with single subtest scaled scores and with two subtests. Estimated GAI are presented for participants diagnosed with dementia (n = 50), traumatic brain injury (n = 20), Huntington's disease (n = 15), Korsakoff's disease (n = 12), chronic alcohol abuse (n = 32), temporal lobectomy (n = 17), and schizophrenia (n = 44). In addition, a small sample of participants without dementia and diagnosed with depression (n = 32) was used as a clinical comparison group. The GAI-E algorithms provided estimates of GAI that closely approximated scores expected for a healthy adult population. The greatest differences between estimated GAI and obtained GAI were observed for the single subtest GAI-E algorithms using the Vocabulary, Information, and Matrix Reasoning subtests. Based on these data, recommendations for the use of the GAI-E algorithms are presented. Published 9 August 2006 in Clin Neuropsychol, 20(3): 365-81.
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