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No Child Left Behind Act 20011
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Showing 16 to 30 of 53 results Save | Export
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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
Reardon, Sean F.; Papay, John P.; Kilbride, Tara; Strunk, Katherine O.; Cowen, Joshua; An, Lily; Donohue, Kate – Stanford Center for Education Policy Analysis, 2019
In this paper we compare two approaches to measuring the average rate at which students learn in a given school or district. One type of measure--longitudinal growth measures--relies on student-level longitudinal data. A second type--cohort growth measures--relies only on repeated aggregated, cross-sectional data. Because student-level data is…
Descriptors: Measurement Techniques, Growth Models, Cohort Analysis, Longitudinal Studies
Samonte, Kelli Marie – ProQuest LLC, 2017
Longitudinal data analysis assumes that scales meet the assumption of longitudinal measurement invariance (i.e., that scales function equivalently across measurement occasions). This simulation study examines the impact of violations to the assumption of longitudinal measurement invariance on growth models and whether modeling the invariance…
Descriptors: Test Bias, Growth Models, Longitudinal Studies, Simulation
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Kim, Minjung; Kwok, Oi-Man; Yoon, Myeongsun; Willson, Victor; Lai, Mark H. C. – Journal of Experimental Education, 2016
This study investigated the optimal strategy for model specification search under the latent growth modeling (LGM) framework, specifically on searching for the correct polynomial mean or average growth model when there is no a priori hypothesized model in the absence of theory. In this simulation study, the effectiveness of different starting…
Descriptors: Statistical Analysis, Growth Models, Simulation, Structural Equation Models
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Reyes, Roland S.; McDermott, Paul A.; Watkins, Marley W.; Rovine, Michael J.; Chao, Jessica L. – School Psychology Review, 2020
This study compared the relative contribution of earliest assessment of preschool children's context-specific problem behaviors with subsequent observations of those behaviors for the prediction of later academic and sociobehavioral performance in first grade. Using a nationally representative sample of low-income children from the Head Start…
Descriptors: Accuracy, Predictive Validity, Preschool Children, Behavior Problems
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Qian, Jiahe – ETS Research Report Series, 2018
The 2-parameter logistic multidimensional item response theory (MIRT) model was employed to model growth for the National Education Longitudinal Study of 1988 (NELS:88). The 3 measurement waves of NELS:88 (base year, first follow-up, and second follow-up) represented 3 dimensions.The inquiry aimed to improve modeling performance growth based on…
Descriptors: Growth Models, Longitudinal Studies, Item Response Theory, National Surveys
Wexler, Danielle – ProQuest LLC, 2019
In elementary school, many children struggle in learning how to read. Some of these struggling readers will be identified to receive special education services as a student with a reading disability (RD), while other students will not be identified to receive such services but will continue to have low reading achievement (LRA). Limited research,…
Descriptors: Reading Achievement, Reading Difficulties, Low Achievement, Longitudinal Studies
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Gagné, Monique H.; Schonert-Reichl, Kimberly; Costigan, Catherine; Guhn, Martin; Shapka, Jennifer D. – Applied Developmental Science, 2019
The study looked at the stratified math and language arts trajectories of foreign-born adolescents (aged 14-19) in British Columbia (BC), Canada, and identified social position factors that predicted this variation. Leveraging data from the Ministry of Health, Ministry of Education and Citizenship and Immigration Canada, the study looked…
Descriptors: Foreign Countries, Immigrants, Adolescents, Academic Achievement
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Marcoulides, Katerina M.; Grimm, Kevin J. – Educational and Psychological Measurement, 2017
Synthesizing results from multiple studies is a daunting task during which researchers must tackle a variety of challenges. The task is even more demanding when studying developmental processes longitudinally and when different instruments are used to measure constructs. Data integration methodology is an emerging field that enables researchers to…
Descriptors: Growth Models, Longitudinal Studies, Mathematics Skills, Achievement Tests
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Liu, Haiyan; Zhang, Zhiyong; Grimm, Kevin J. – Grantee Submission, 2016
Growth curve modeling provides a general framework for analyzing longitudinal data from social, behavioral, and educational sciences. Bayesian methods have been used to estimate growth curve models, in which priors need to be specified for unknown parameters. For the covariance parameter matrix, the inverse Wishart prior is most commonly used due…
Descriptors: Bayesian Statistics, Computation, Statistical Analysis, Growth Models
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
Marquez, Jocabed G. – ProQuest LLC, 2018
The United States faces high demand for science, technology, engineering, or mathematics (STEM) professionals and a scarce supply of individuals who pursue STEM careers, especially minority populations in the U.S with proficiency in a language other than English. The primary goal of this research was to determine the impact of use of Spanish in…
Descriptors: Longitudinal Studies, Executive Function, Mathematics Achievement, Science Achievement
Schulte, Ann C.; Stevens, Joseph J.; Nese, Joseph F. T.; Yel, Nedim; Tindal, Gerald; Elliott, Stephen N. – National Center on Assessment and Accountability for Special Education, 2018
This technical report is one of a series of four technical reports that describe the results of a study comparing eight alternative models for estimating school academic achievement using data from the Arizona, North Carolina, Oregon, and Pennsylvania accountability systems. The purpose of these reports was to evaluate a broad range of models…
Descriptors: School Effectiveness, Models, Computation, Comparative Analysis
Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Yel, Nedim; Anderson, Daniel; Matta, Tyler; Elliott, Stephen N. – National Center on Assessment and Accountability for Special Education, 2018
This technical report is one of a series of four technical reports that describe the results of a study comparing eight alternative models for estimating school academic achievement using data from the Arizona, North Carolina, Oregon, and Pennsylvania accountability systems. The purpose of these reports was to evaluate a broad range of models…
Descriptors: School Effectiveness, Models, Computation, Comparative Analysis
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