Open AccessUsing latent class analysis to identify academic and behavioral risk status in elementary students.
Author(s) -
Kathleen R. King,
Erica S. Lembke,
Wendy M. Reinke
Publication year - 2016
Publication title -
school psychology quarterly
Language(s) - English
Resource type - Journals
eISSN - 1939-1560
pISSN - 1045-3830
DOI - 10.1037/spq0000111
Subject(s) - tier 2 network , academic achievement , psycinfo , psychology , latent class model , at risk students , test (biology) , intervention (counseling) , class (philosophy) , response to intervention , tier 1 network , sample (material) , mathematics education , predictive validity , achievement test , developmental psychology , clinical psychology , standardized test , special education , medline , statistics , psychiatry , mathematics , artificial intelligence , law , chemistry , world wide web , computer science , biology , telecommunications , paleontology , the internet , chromatography , political science
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