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Showing 1 to 15 of 19 results Save | Export
Joshua B. Gilbert; James G. Soland; Benjamin W. Domingue – Annenberg Institute for School Reform at Brown University, 2025
Value-Added Models (VAMs) are both common and controversial in education policy and accountability research. While the sensitivity of VAMs to model specification and covariate selection is well documented, the extent to which test scoring methods (e.g., mean scores vs. IRT-based scores) may affect VA estimates is less studied. We examine the…
Descriptors: Value Added Models, Tests, Testing, Scoring
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Donoghue, John R.; McClellan, Catherine A.; Hess, Melinda R. – ETS Research Report Series, 2022
When constructed-response items are administered for a second time, it is necessary to evaluate whether the current Time B administration's raters have drifted from the scoring of the original administration at Time A. To study this, Time A papers are sampled and rescored by Time B scorers. Commonly the scores are compared using the proportion of…
Descriptors: Item Response Theory, Test Construction, Scoring, Testing
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Liu, Ren; Liu, Haiyan; Shi, Dexin; Jiang, Zhehan – Educational and Psychological Measurement, 2022
Assessments with a large amount of small, similar, or often repetitive tasks are being used in educational, neurocognitive, and psychological contexts. For example, respondents are asked to recognize numbers or letters from a large pool of those and the number of correct answers is a count variable. In 1960, George Rasch developed the Rasch…
Descriptors: Classification, Models, Statistical Distributions, Scores
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Arthurs, Noah; Stenhaug, Ben; Karayev, Sergey; Piech, Chris – International Educational Data Mining Society, 2019
Understanding exam score distributions has implications for item response theory (IRT), grade curving, and downstream modeling tasks such as peer grading. Historically, grades have been assumed to be normally distributed, and to this day the normal is the ubiquitous choice for modeling exam scores. While this is a good assumption for tests…
Descriptors: Grades (Scholastic), Scores, Statistical Distributions, Models
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Li, Zhen; Cai, Li – Grantee Submission, 2017
In standard item response theory (IRT) applications, the latent variable is typically assumed to be normally distributed. If the normality assumption is violated, the item parameter estimates can become biased. Summed score likelihood based statistics may be useful for testing latent variable distribution fit. We develop Satorra-Bentler type…
Descriptors: Scores, Goodness of Fit, Statistical Distributions, Item Response Theory
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Kastberg, David; Murray, Gordon; Ferraro, David; Arieira, Carlos; Roey, Shep; Mamedova, Saida; Liao, Yuqi – National Center for Education Statistics, 2021
The Program for International Student Assessment Young Adult Follow-up Study (PISA YAFS) is a follow-up study with students who participated in PISA 2012 in the United States. The study is designed to measure how performance on PISA 2012 relates to subsequent measures of outcomes and skills of young adults on an online assessment, Education and…
Descriptors: Foreign Countries, Achievement Tests, Secondary School Students, Young Adults
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Ho, Andrew D.; Yu, Carol C. – Educational and Psychological Measurement, 2015
Many statistical analyses benefit from the assumption that unconditional or conditional distributions are continuous and normal. More than 50 years ago in this journal, Lord and Cook chronicled departures from normality in educational tests, and Micerri similarly showed that the normality assumption is met rarely in educational and psychological…
Descriptors: Statistics, Scores, Statistical Distributions, Tests
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Kim, Seonghoon – Journal of Educational Measurement, 2013
With known item response theory (IRT) item parameters, Lord and Wingersky provided a recursive algorithm for computing the conditional frequency distribution of number-correct test scores, given proficiency. This article presents a generalized algorithm for computing the conditional distribution of summed test scores involving real-number item…
Descriptors: Item Response Theory, Scores, Computation, Mathematics
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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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Bramley, Tom – Research in Mathematics Education, 2017
This study compared models of assessment structure for achieving differentiation across the range of examinee attainment in the General Certificate of Secondary Education (GCSE) examination taken by 16-year-olds in England. The focus was on the "adjacent levels" model, where papers are targeted at three specific non-overlapping ranges of…
Descriptors: Foreign Countries, Mathematics Education, Student Certification, Student Evaluation
Quesen, Sarah – ProQuest LLC, 2016
When studying differential item functioning (DIF) with students with disabilities (SWD) focal groups typically suffer from small sample size, whereas the reference group population is usually large. This makes it possible for a researcher to select a sample from the reference population to be similar to the focal group on the ability scale. Doing…
Descriptors: Test Items, Academic Accommodations (Disabilities), Testing Accommodations, Disabilities
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Hayes, Kevin – Teaching Statistics: An International Journal for Teachers, 2004
This article demonstrates that the lower bound for the most deviant Z score and the upper bound for the sample standard deviation are attained simultaneously.
Descriptors: Statistical Analysis, Scores, Item Response Theory, Probability
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Ferrando, Pere J.; Lorenzo-Seva, Urbano – Educational and Psychological Measurement, 2001
Describes a Windows program for checking the suitability of unidimensional logistic item response models for binary and ordered polytomous responses with respect to a given set of data. The program is based on predicting the observed test score distributions from the item characteristic curves. (SLD)
Descriptors: Computer Software, Item Response Theory, Mathematical Models, Prediction
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van der Linden, Wim J.; Luecht, Richard M. – Psychometrika, 1998
Derives a set of linear conditions of item-response functions that guarantees identical observed-score distributions on two test forms. The conditions can be added as constraints to a linear programming model for test assembly. An example illustrates the use of the model for an item pool from the Law School Admissions Test (LSAT). (SLD)
Descriptors: Equated Scores, Item Banks, Item Response Theory, Linear Programming
Meijer, Rob R.; van Krimpen-Stoop, Edith M. L. A. – 1998
Several person-fit statistics have been proposed to detect item score patterns that do not fit an item response theory model. To classify response patterns as not fitting a model, a distribution of a person-fit statistic is needed. The null distributions of several fit statistics have been investigated using conventionally administered tests, but…
Descriptors: Ability, Adaptive Testing, Foreign Countries, Item Response Theory
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