Using growth-based approaches to study the early psychoeducational development of young children with disabilities



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Purpose: This research used data collected as part of the Pre-Elementary Educational Longitudinal Study (PEELS) to investigate the patterns of language and literacy and math development for young children with disabilities as well as to identify and describe unobserved subpopulations based on developmental trajectories and how subpopulation classification mediates the effects of covariates on the development. Method: Conditional multiple-indicator growth models and growth mixture models were fit using standardized achievement test scores for a sample of young children with disabilities (n = 422). The covariates included in this research were ethnicity, metropolitan status, family income, and type of early learning setting. Results: Family income had a significant effect for both models at Wave 1 and the type of early learning experience was significant for both models at Wave 3. Hispanic children had lower language and literacy ability at age three when compared to Caucasian children. Hispanic children also developed language and literacy ability at a slower rate than Caucasian children. Metropolitan status did not have a significant effect development the language and literacy ability or math ability.



Young children with disabilities, Emergent language and literacy development, Math development, Latent curve modeling, Growth mixture modeling