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Showing 1 to 15 of 18 results Save | Export
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Cornelis Potgieter; Xin Qiao; Akihito Kamata; Yusuf Kara – Grantee Submission, 2024
As part of the effort to develop an improved oral reading fluency (ORF) assessment system, Kara et al. (2020) estimated the ORF scores based on a latent variable psychometric model of accuracy and speed for ORF data via a fully Bayesian approach. This study further investigates likelihood-based estimators for the model-derived ORF scores,…
Descriptors: Oral Reading, Reading Fluency, Scores, Psychometrics
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Cornelis Potgieter; Xin Qiao; Akihito Kamata; Yusuf Kara – Journal of Educational Measurement, 2024
As part of the effort to develop an improved oral reading fluency (ORF) assessment system, Kara et al. estimated the ORF scores based on a latent variable psychometric model of accuracy and speed for ORF data via a fully Bayesian approach. This study further investigates likelihood-based estimators for the model-derived ORF scores, including…
Descriptors: Oral Reading, Reading Fluency, Scores, Psychometrics
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Hall, Garret J.; Kaplan, David; Albers, Craig A. – Learning Disabilities Research & Practice, 2022
Bayesian latent change score modeling (LCSM) was used to compare models of triannual (fall, winter, spring) change on elementary math computation and concepts/applications curriculum-based measures. Data were collected from elementary students in Grades 2-5, approximately 700 to 850 students in each grade (47%-54% female; 78%-79% White, 10%-11%…
Descriptors: Learning Disabilities, Students with Disabilities, Elementary School Students, Mathematics Skills
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Kim, Sooyeon; Moses, Tim; Yoo, Hanwook Henry – ETS Research Report Series, 2015
The purpose of this inquiry was to investigate the effectiveness of item response theory (IRT) proficiency estimators in terms of estimation bias and error under multistage testing (MST). We chose a 2-stage MST design in which 1 adaptation to the examinees' ability levels takes place. It includes 4 modules (1 at Stage 1, 3 at Stage 2) and 3 paths…
Descriptors: Item Response Theory, Computation, Statistical Bias, Error of Measurement
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Lockwood, J. R.; McCaffrey, Daniel F. – Journal of Educational and Behavioral Statistics, 2014
A common strategy for estimating treatment effects in observational studies using individual student-level data is analysis of covariance (ANCOVA) or hierarchical variants of it, in which outcomes (often standardized test scores) are regressed on pretreatment test scores, other student characteristics, and treatment group indicators. Measurement…
Descriptors: Error of Measurement, Scores, Statistical Analysis, Computation
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Johnson, Timothy R. – Applied Psychological Measurement, 2013
One of the distinctions between classical test theory and item response theory is that the former focuses on sum scores and their relationship to true scores, whereas the latter concerns item responses and their relationship to latent scores. Although item response theory is often viewed as the richer of the two theories, sum scores are still…
Descriptors: Item Response Theory, Scores, Computation, Bayesian Statistics
Foorman, Barbara R.; Petscher, Yaacov – Society for Research on Educational Effectiveness, 2011
In Florida, mean proficiency scores are reported on the Florida Comprehensive Achievement Test (FCAT) as well as recommended learning gains from the developmental scale score. Florida now has another within-year measure of growth in reading comprehension from the Florida Assessments for Instruction in Reading (FAIR). The FAIR reading comprehension…
Descriptors: Achievement Tests, Reading Comprehension, Reading Tests, Scores
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Ligtvoet, Rudy – Psychometrika, 2012
In practice, the sum of the item scores is often used as a basis for comparing subjects. For items that have more than two ordered score categories, only the partial credit model (PCM) and special cases of this model imply that the subjects are stochastically ordered on the common latent variable. However, the PCM is very restrictive with respect…
Descriptors: Simulation, Item Response Theory, Comparative Analysis, Scores
Md Desa, Zairul Nor Deana – ProQuest LLC, 2012
In recent years, there has been increasing interest in estimating and improving subscore reliability. In this study, the multidimensional item response theory (MIRT) and the bi-factor model were combined to estimate subscores, to obtain subscores reliability, and subscores classification. Both the compensatory and partially compensatory MIRT…
Descriptors: Item Response Theory, Computation, Reliability, Classification
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Schochet, Peter Z.; Chiang, Hanley S. – Journal of Educational and Behavioral Statistics, 2013
This article addresses likely error rates for measuring teacher and school performance in the upper elementary grades using value-added models applied to student test score gain data. Using a realistic performance measurement system scheme based on hypothesis testing, the authors develop error rate formulas based on ordinary least squares and…
Descriptors: Classification, Measurement, Elementary School Teachers, Elementary Schools
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Petscher, Yaacov; Kershaw, Sarah; Koon, Sharon; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for…
Descriptors: Reading Comprehension, Reading Achievement, Elementary School Students, Secondary School Students
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Petscher, Yaacov; Kershaw, Sarah; Koon, Sharon; Foorman, Barbara R. – Regional Educational Laboratory Southeast, 2014
Districts and schools use progress monitoring to assess student progress, to identify students who fail to respond to intervention, and to further adapt instruction to student needs. Researchers and practitioners often use progress monitoring data to estimate student achievement growth (slope) and evaluate changes in performance over time for…
Descriptors: Response to Intervention, Achievement Gains, High Stakes Tests, Prediction
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Mariano, Louis T.; McCaffrey, Daniel F.; Lockwood, J. R. – Journal of Educational and Behavioral Statistics, 2010
There is an increasing interest in using longitudinal measures of student achievement to estimate individual teacher effects. Current multivariate models assume each teacher has a single effect on student outcomes that persists undiminished to all future test administrations (complete persistence [CP]) or can diminish with time but remains…
Descriptors: Persistence, Academic Achievement, Data Analysis, Teacher Influence
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Choi, Kilchan; Seltzer, Michael – Journal of Educational and Behavioral Statistics, 2010
In studies of change in education and numerous other fields, interest often centers on how differences in the status of individuals at the start of a period of substantive interest relate to differences in subsequent change. In this article, the authors present a fully Bayesian approach to estimating three-level Hierarchical Models in which latent…
Descriptors: Simulation, Computation, Models, Bayesian Statistics
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Hoffman, Bobby; Schraw, Gregory – Educational Psychologist, 2010
The purpose of this article is to clarify conceptions, definitions, and applications of learning and problem-solving efficiency. Conceptions of efficiency vary within the field of educational psychology, and there is little consensus as to how to define, measure, and interpret the efficiency construct. We compare three diverse models that differ…
Descriptors: Educational Psychology, Efficiency, Problem Solving, Models
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