Standard Score Comparison 2.0: Second-generation learning disability regression software

As states increasingly adopt actuarial models to aid learning disability (LD) identification, microcomputer programs are being used to accurately measure the primary LD criterion: severe discrepancies between IQ and achievement. First-generation programs offered little flexibility in regression parameters and user-defined options. This paper describes Standard Score Comparison 2.0 (SSC 2.0), a second-generation regression program that calculates multiple discrepancies, and provides options for Type I error rates, SEM confidence levels, correction for multiple comparisons, and the cut-off value that defines severe discrepancy. Application of SSC 2.0 to non-LD areas and potential features of third-generation software are discussed.