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We used data simulations to test whether composites consisting of cohesive subtest scores are more accurate than composites consisting of divergent subtest scores. We demonstrate that when multivariate normality holds, divergent and cohesive scores are equally accurate. Furthermore, excluding divergent scores results in biased estimates of construct scores. We show that obtaining divergent scores should prompt additional testing under some conditions. Although there are many valid reasons to exclude scores from consideration (e.g., malingering, fatigue, and misunderstood directions), no score should be removed from a composite simply because it is different from other scores in the composite. [ABSTRACT FROM AUTHOR]

The charge of an educational diagnostician is to serve the educational needs of our exceptional children and youth. In order to do so, these professionals must possess a strong knowledge-base and understanding of the pertinent steps and processes of identification for any student who may be suspected of having a specific learning disability (SLD), as defined by the Individuals with Disabilities Education Improvement Act (2004). While there are many methodologies utilized in Texas, this article will focus on the impact of Cattell-Horn-Carroll (CHC) theory to the recommendation of SLD determination. [ABSTRACT FROM AUTHOR]

The Individuals with Disabilities Education Act allows three methods of determining whether a student qualifies for special education as a student with a specific learning disability (SLD). The first and most controversial is the Discrepancy model, which requires a significant discrepancy between the student's intellectual ability and academic achievement. The second is the Response to Intervention (RTI) model, which utilizes a process to assess a student's response to scientific, researched-based interventions. The third method involves reviewing the student's unique pattern of cognitive strengths and weaknesses (PSW) that result in academic deficits. The present article reviews the research regarding the strengths and weaknesses of each model. Furthermore, due to the recent emergence of PSW models, this article concludes with the authors' recommendations for further research prior to implementation of the PSW approach. [ABSTRACT FROM AUTHOR]