Assessment for Effective Intervention, Ahead of Print.
This article describes the development and psychometric properties of a new Dyslexia Marker Test for Children (Dysmate-C). The test was designed to identify Norwegian students who need special instructional attention. The computerized test includes measures of letter knowledge, phoneme awareness, rapid automatized naming, working memory, decoding, and spelling skills. Data were collected data from a sample of more than 1,100 students. Item response theory (IRT) was used for the psychometric evaluation, and principal component analysis for checking uni-dimensionality. IRT was further used to select and remove items, which significantly shortened the test battery without sacrificing reliability or discriminating ability. Cronbach’s alphas ranged between .84 and .95. Validity was established by examining how well the Dysmate-C identified students already diagnosed with dyslexia. Logistic regression and receiver operating characteristic (ROC) curve analyses indicated good to excellent accuracy in separating children with dyslexia from typical children (area under curve [AUC] = .92). The Dysmate-C meets the standards for reliability and validity. The use of regression-based norms, voice-over instructions, easy scoring procedures, accurate timing, and automatic computation of scores, make the test a useful tool. It may be used in as part screening procedure, and as part of a diagnostic assessment. Limitations and practical implications are discussed.