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Nam, Yeji; Hong, Sehee – Educational and Psychological Measurement, 2021
This study investigated the extent to which class-specific parameter estimates are biased by the within-class normality assumption in nonnormal growth mixture modeling (GMM). Monte Carlo simulations for nonnormal GMM were conducted to analyze and compare two strategies for obtaining unbiased parameter estimates: relaxing the within-class normality…
Descriptors: Probability, Models, Statistical Analysis, Statistical Distributions
Jinyong Hahn; John D. Singleton; Nese Yildiz – Annenberg Institute for School Reform at Brown University, 2023
Panel or grouped data are often used to allow for unobserved individual heterogeneity in econometric models via fixed effects. In this paper, we discuss identification of a panel data model in which the unobserved heterogeneity both enters additively and interacts with treatment variables. We present identification and estimation methods for…
Descriptors: Teacher Effectiveness, Models, Computation, Statistical Analysis
Contini, Dalit; Cugnata, Federica – Large-scale Assessments in Education, 2020
The development of international surveys on children's learning like PISA, PIRLS and TIMSS--delivering comparable achievement measures across educational systems--has revealed large cross-country variability in average performance and in the degree of inequality across social groups. A key question is whether and how institutional differences…
Descriptors: International Assessment, Achievement Tests, Scores, Family Characteristics
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
Johnson, Matthew T.; Lipscomb, Stephen; Gill, Brian – Journal of Research on Educational Effectiveness, 2015
Teacher value-added models (VAMs) must isolate teachers' contributions to student achievement to be valid. Well-known VAMs use different specifications, however, leaving policymakers with little clear guidance for constructing a valid model. We examine the sensitivity of teacher value-added estimates under different models based on whether they…
Descriptors: Teacher Effectiveness, Teacher Influence, Academic Achievement, Models
Franco, M. Suzanne; Seidel, Kent – Education and Urban Society, 2014
Value-added approaches for attributing student growth to teachers often use weighted estimates of building-level factors based on "typical" schools to represent a range of community, school, and other variables related to teacher and student work that are not easily measured directly. This study examines whether such estimates are likely…
Descriptors: Teacher Effectiveness, Academic Achievement, Models, Computation
Wagenmakers, Eric-Jan; Lodewyckx, Tom; Kuriyal, Himanshu; Grasman, Raoul – Cognitive Psychology, 2010
In the field of cognitive psychology, the "p"-value hypothesis test has established a stranglehold on statistical reporting. This is unfortunate, as the "p"-value provides at best a rough estimate of the evidence that the data provide for the presence of an experimental effect. An alternative and arguably more appropriate measure of evidence is…
Descriptors: Student Evaluation, Psychologists, Hypothesis Testing, Cognitive Psychology
Lipscomb, Stephen; Chiang, Hanley; Gill, Brian – Mathematica Policy Research, Inc., 2012
The Commonwealth of Pennsylvania plans to develop a new statewide evaluation system for teachers and principals in its public schools by school year 2013-2014. To inform the development of this evaluation system, the Team Pennsylvania Foundation (Team PA) undertook the first phase of the Pennsylvania Teacher and Principal Evaluation…
Descriptors: Academic Achievement, Models, Outcomes of Education, Teacher Evaluation
Lipscomb, Stephen; Chiang, Hanley; Gill, Brian – Mathematica Policy Research, Inc., 2012
The Commonwealth of Pennsylvania plans to develop a new statewide evaluation system for teachers and principals in its public schools by school year 2013-2014. To inform the development of this evaluation system, the Team Pennsylvania Foundation (Team PA) undertook the first phase of the Pennsylvania Teacher and Principal Evaluation…
Descriptors: Academic Achievement, Models, Outcomes of Education, Teacher Evaluation
Johnson, Matthew; Lipscomb, Stephen; Gill, Brian; Booker, Kevin; Bruch, Julie – Mathematica Policy Research, Inc., 2012
At the request of Pittsburgh Public Schools (PPS) and the Pittsburgh Federation of Teachers (PFT), Mathematica has developed value-added models (VAMs) that aim to estimate the contributions of individual teachers, teams of teachers, and schools to the achievement growth of their students. The authors' work in estimating value-added in Pittsburgh…
Descriptors: Public Schools, Outcomes of Education, Academic Achievement, Teacher Effectiveness
Lipscomb, Stephen; Teh, Bing-ru; Gill, Brian; Chiang, Hanley; Owens, Antoniya – Mathematica Policy Research, Inc., 2010
This report summarizes research findings and implementation practices for teacher and principal value-added models (VAMs), as a first step in the Team Pennsylvania Foundation's (Team PA) pilot project to inform the development of a full, statewide model evaluation system. We have selected 21 studies that represent key issues and findings in the…
Descriptors: Pilot Projects, Outcomes of Education, Principals, Models
Isenberg, Eric; Hock, Heinrich – Mathematica Policy Research, Inc., 2012
In this report, the authors describe the value-added models used as part of teacher evaluation systems in the District of Columbia Public Schools (DCPS) and in eligible DC charter schools participating in Race to the Top. They estimated (1) teacher effectiveness in DCPS and eligible DC charter schools during the 2011-2012 school year; and (2)…
Descriptors: Value Added Models, Teacher Evaluation, Public Schools, Urban Schools
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