Using latent class analysis to identify academic and behavioral risk status in elementary students.

Abstract

Identifying classes of children on the basis of academic and behavior risk may have important implications for the allocation of intervention resources within Response to Intervention (RTI) and Multi-Tiered System of Support (MTSS) models. Latent class analysis (LCA) was conducted with a sample of 517 third grade students. Fall screening scores in the areas of reading, mathematics, and behavior were used as indicators of success on an end of year statewide achievement test. Results identified 3 subclasses of children, including a class with minimal academic and behavioral concerns (Tier 1; 32% of the sample), a class at-risk for academic problems and somewhat at-risk for behavior problems (Tier 2; 37% of the sample), and a class with significant academic and behavior problems (Tier 3; 31%). Each class was predictive of end of year performance on the statewide achievement test, with the Tier 1 class performing significantly higher on the test than the Tier 2 class, which in turn scored significantly higher than the Tier 3 class. The results of this study indicated that distinct classes of children can be determined through brief screening measures and are predictive of later academic success. Further implications are discussed for prevention and intervention for students at risk for academic failure and behavior problems. (PsycINFO Database Record