title: Can children with language impairment be accurately identified using temporal processing measures? A simulation study.
abstract: Three simulation experiments were conducted to determine the basis of the high predictive accuracy (98%) of temporal processing variables for the identification of language impairment obtained by Tallal, Stark, and Mellits (1985). In the first two experiments, the stepwise discriminant analysis using a set of 160 arrays of random numbers to predict a dichotomous language status (either normal or disordered) resulted in an average accuracy rate of 86.3% in contrast with the 98% rate obtained by Tallal, Stark, and Mellits. The third experiment showed that a 95% accuracy rate could be obtained from an array of 160 variables that each may only account for about 1.5% variance in the language ability. These results emphasize the need for confirmatory studies when large data sets are used to identify a small set of predictor variables.
authors.affiliation: The University of Iowa, Department of Speech and Pathology, Iowa City, 52242, USA. suyang-zhang@uiowa.edu
authors.forename: X
authors.initials: X
authors.lastname: Zhang
authors.forename: J B
authors.initials: JB
authors.lastname: Tomblin
mesh_terms: D002648:Child; D006801:Humans; D007806:Language Disorders / Q000175:diagnosis*; D008606:Mental Processes / Q000502:physiology; D011237:Predictive Value of Tests; D011897:Random Allocation; D013997:Time Factors