Congressional vagueness in the definition of learning disability has resulted in numerous statistical definitions based on achievement-ability test differences. Previous statistical research has helped to clarify the issues and to eliminate some inadequate models. This paper examines three models still considered useful to this point. The models are the prediction model, true score regression model, and prescore partialling model. Results of the analysis conducted here 'provide support for the regression model as the simplest to use and most efficient statistically.
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