A Latent Transition Analysis of English Learners With Reading Disabilities: Do Measures of Cognition Add to Predictions of Late Emerging Risk Status?. Issue 2 (April 2017) - Swanson, H. Lee
Abstract : The purpose of this cohort sequential study was to extend previously reported latent transition analyses conducted bySwanson, Kudo, and Guzman-Orth (2016) by determining the role of cognitive measures in identifying English learners (EL) at risk for late emerging reading disabilities (LERD). To this end, EL students ( N = 450) in Grades 1, 2, and 3 at Wave 1 were administered a battery of reading, vocabulary, and cognitive measures (short-term memory [STM], working memory [WM], rapid naming, and random letter and number generation) in both Spanish and English. These same measures were administered 1 and 2 years later. Four important findings emerged. First, inclusion of cognitive measures provided a better fit to the data toward identifying latent class transitions than with reading and vocabulary measures alone. Second, the prevalence of children identified as at risk for reading disabilities in the earlier testing waves within each cohort was stable across testing waves (97% chance of maintaining the classification). Third, the latent class labeled as inattentive in Wave 1 showed the largest transition probabilities for LERD, especially for the cohorts transitioning from Grades 3 to 4. Finally, the chances of "not" being identified as LERD were significantly related to performance on L1 and/or L2 measures of cognition (English STM, Spanish WM, and Spanish naming Speed), reading (Spanish word identification, English passage comprehension) and vocabulary (English vocabulary and English syntax). The results support the notion that statistically distinct latent classes emerge under the umbrella of reading proficiency, but those children identified as late emerging poor readers were related to another latent class of risk group (inattentive children) rather than to a latent class of good readers. Abstract : Supplemental Digital Content is Available in the Text.