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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
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
Monroe, Scott; Cai, Li – Educational Measurement: Issues and Practice, 2015
Student growth percentiles (SGPs, Betebenner, 2009) are used to locate a student's current score in a conditional distribution based on the student's past scores. Currently, following Betebenner (2009), quantile regression (QR) is most often used operationally to estimate the SGPs. Alternatively, multidimensional item response theory (MIRT) may…
Descriptors: Item Response Theory, Reliability, Growth Models, Computation
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
Stevens, Joseph J.; Nese, Joseph F. T.; Schulte, Ann C.; Tindal, Gerald; Yel, Nedim; Anderson, Daniel; Matta, Tyler; Elliott, Stephen N. – National Center on Assessment and Accountability for Special Education, 2017
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
Schulte, Ann C.; Nese, Joseph F. T.; Stevens, Joseph J.; Yel, Nedim; Tindal, Gerald; Anderson, Daniel; Elliott, Stephen N. – National Center on Assessment and Accountability for Special Education, 2017
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
Braun, Henry; Qu, Yanxuan – ETS Research Report Series, 2008
This paper reports on a study conducted to investigate the consistency of the results between 2 approaches to estimating school effectiveness through value-added modeling. Estimates of school effects from the layered model employing item response theory (IRT) scaled data are compared to estimates derived from a discrete growth model based on the…
Descriptors: Value Added Models, School Effectiveness, Robustness (Statistics), Computation