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Ethan R. Van Norman; Emily R. Forcht – Journal of Education for Students Placed at Risk, 2024
This study evaluated the forecasting accuracy of trend estimation methods applied to time-series data from computer adaptive tests (CATs). Data were collected roughly once a month over the course of a school year. We evaluated the forecasting accuracy of two regression-based growth estimation methods (ordinary least squares and Theil-Sen). The…
Descriptors: Data Collection, Predictive Measurement, Predictive Validity, Predictor Variables
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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
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Quirk, Matthew; Grimm, Ryan; Furlong, Michael J.; Nylund-Gibson, Karen; Swami, Sruthi – Journal of Educational Psychology, 2016
This study utilized latent class analysis (LCA) to identify 5 discernible profiles of Latino children's (N = 1,253) social-emotional, physical, and cognitive school readiness at the time of kindergarten entry. In addition, a growth mixture modeling (GMM) approach was used to identify 3 unique literacy achievement trajectories, across Grades 2-5,…
Descriptors: Hispanic Americans, Kindergarten, Young Children, School Readiness
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
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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
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Almond, Russell G.; Sinharay, Sandip – ETS Research Report Series, 2012
To answer questions about how students' proficiencies are changing over time, educational researchers are looking for data sources that span many years. Clearly, for answering questions about student growth, a longitudinal study--in which a single sample is followed over many years--is preferable to repeated cross-sectional samples--in which a…
Descriptors: Educational Research, Case Studies, Research Methodology, Literature Reviews