Learning Disability Classification by Bayesian Aggregation of Test Results

Abstract

The feasibility of the Bayesian approach to screening for learning disability proposed by Wissink, Kass, and Ferrell (1975) is further explored. Two matched groups of children, one with and one without learning disability, were given tests related to component disabilities previously identified as being diagnostic. The probability that each child has learning disability was calculated from the test results according to the Bayesian procedure and on that basis the children were reclassified. The Bayesian method compared favorably with discriminant analysis in accuracy and is more easily applied to screening. Moreover, the lack of independence in the data did not seriously affect the results. It is concluded that the method warrants further study.