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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
Schochet, Peter Z. – Journal of Educational and Behavioral Statistics, 2013
In school-based randomized control trials (RCTs), a common design is to follow student cohorts over time. For such designs, education researchers usually focus on the place-based (PB) impact parameter, which is estimated using data collected on all students enrolled in the study schools at each data collection point. A potential problem with this…
Descriptors: Student Mobility, Scientific Methodology, Research Design, Intervention
Briggs, Derek C.; Domingue, Ben – Journal of Educational and Behavioral Statistics, 2013
It is often assumed that a vertical scale is necessary when value-added models depend upon the gain scores of students across two or more points in time. This article examines the conditions under which the scale transformations associated with the vertical scaling process would be expected to have a significant impact on normative interpretations…
Descriptors: Evaluation Methods, Scaling, Scores, Achievement Tests
Boyd, Donald; Lankford, Hamilton; Loeb, Susanna; Wyckoff, James – Journal of Educational and Behavioral Statistics, 2013
Test-based accountability as well as value-added asessments and much experimental and quasi-experimental research in education rely on achievement tests to measure student skills and knowledge. Yet, we know little regarding fundamental properties of these tests, an important example being the extent of measurement error and its implications for…
Descriptors: Accountability, Educational Research, Educational Testing, Error of Measurement