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Soland, James; Thum, Yeow Meng – Journal of Research on Educational Effectiveness, 2022
Sources of longitudinal achievement data are increasing thanks partially to the expansion of available interim assessments. These tests are often used to monitor the progress of students, classrooms, and schools within and across school years. Yet, few statistical models equipped to approximate the distinctly seasonal patterns in the data exist,…
Descriptors: Academic Achievement, Longitudinal Studies, Data Use, Computation
Choi, Kilchan; Kim, Jinok – Journal of Educational and Behavioral Statistics, 2019
This article proposes a latent variable regression four-level hierarchical model (LVR-HM4) that uses a fully Bayesian approach. Using multisite multiple-cohort longitudinal data, for example, annual assessment scores over grades for students who are nested within cohorts within schools, the LVR-HM4 attempts to simultaneously model two types of…
Descriptors: Regression (Statistics), Hierarchical Linear Modeling, Longitudinal Studies, Cohort Analysis
Kruk, Richard S.; Luther Ruban, Cassia – Journal of Learning Disabilities, 2018
Visual processes in Grade 1 were examined for their predictive influences in nonalphanumeric and alphanumeric rapid naming (RAN) in 51 poor early and 69 typical readers. In a lagged design, children were followed longitudinally from Grade 1 to Grade 3 over 5 testing occasions. RAN outcomes in early Grade 2 were predicted by speeded and nonspeeded…
Descriptors: Naming, Reading Difficulties, Grade 1, Grade 2
Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Elliott, Stephen N. – Journal of Special Education, 2017
Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state's mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four…
Descriptors: Classification, Achievement Gains, Special Needs Students, Mathematics Achievement
Herrera, Sarah; Zhou, Chengfu; Petscher, Yaacov – Regional Educational Laboratory Southeast, 2017
The 2001 authorization of the No Child Left Behind Act and its standards and accountability requirements generated interest among state education agencies in Florida, Mississippi, and North Carolina, which are served by the Regional Educational Laboratory Southeast, in monitoring changes in student reading and math proficiency at the school level.…
Descriptors: Reading Achievement, Mathematics Achievement, Trend Analysis, Achievement Gap
Petscher, Yaacov; Quinn, Jamie M.; Wagner, Richard K. – Developmental Psychology, 2016
Conceptualizations of developmental trends are driven by the particular method used to analyze the period of change of interest. Various techniques exist to analyze developmental data, including individual growth curve analysis in observed and latent frameworks, cross-lagged regression to assess interrelations among variables, and multilevel…
Descriptors: Individual Development, Correlation, Longitudinal Studies, Oral Reading