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Cole, Ki; Paek, Insu – Measurement: Interdisciplinary Research and Perspectives, 2022
Statistical Analysis Software (SAS) is a widely used tool for data management analysis across a variety of fields. The procedure for item response theory (PROC IRT) is one to perform unidimensional and multidimensional item response theory (IRT) analysis for dichotomous and polytomous data. This review provides a summary of the features of PROC…
Descriptors: Item Response Theory, Computer Software, Item Analysis, Statistical Analysis
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Zehner, Fabian; Eichmann, Beate; Deribo, Tobias; Harrison, Scott; Bengs, Daniel; Andersen, Nico; Hahnel, Carolin – Journal of Educational Data Mining, 2021
The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal…
Descriptors: National Competency Tests, Engineering Education, Data Collection, Data Analysis
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Choi, Youn-Jeng; Asilkalkan, Abdullah – Measurement: Interdisciplinary Research and Perspectives, 2019
About 45 R packages to analyze data using item response theory (IRT) have been developed over the last decade. This article introduces these 45 R packages with their descriptions and features. It also describes possible advanced IRT models using R packages, as well as dichotomous and polytomous IRT models, and R packages that contain applications…
Descriptors: Item Response Theory, Data Analysis, Computer Software, Test Bias
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Boone, William J. – CBE - Life Sciences Education, 2016
This essay describes Rasch analysis psychometric techniques and how such techniques can be used by life sciences education researchers to guide the development and use of surveys and tests. Specifically, Rasch techniques can be used to document and evaluate the measurement functioning of such instruments. Rasch techniques also allow researchers to…
Descriptors: Item Response Theory, Psychometrics, Science Education, Educational Research
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Arenson, Ethan A.; Karabatsos, George – Grantee Submission, 2017
Item response models typically assume that the item characteristic (step) curves follow a logistic or normal cumulative distribution function, which are strictly monotone functions of person test ability. Such assumptions can be overly-restrictive for real item response data. We propose a simple and more flexible Bayesian nonparametric IRT model…
Descriptors: Bayesian Statistics, Item Response Theory, Nonparametric Statistics, Models
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Draxler, Clemens – Educational Research and Evaluation, 2011
This article discusses the application of logit models for the analyses of 2-way categorical observations. The models described are generalized linear models using the logit link function. One of the models is the Rasch model (Rasch, 1960). The objective is to test hypotheses of marginal and conditional independence between explanatory quantities…
Descriptors: Models, Item Response Theory, Educational Research, Hypothesis Testing
New Meridian Corporation, 2020
The purpose of this report is to describe the technical qualities of the 2018-2019 operational administration of the English language arts/literacy (ELA/L) and mathematics summative assessments in grades 3 through 8 and high school. The ELA/L assessments focus on reading and comprehending a range of sufficiently complex texts independently and…
Descriptors: Language Arts, Literacy Education, Mathematics Education, Summative Evaluation
New Meridian Corporation, 2020
The purpose of this report is to describe the technical qualities of the 2018-2019 operational administration of the English language arts/literacy (ELA/L) and mathematics assessments in grades 3 through 8 and high school. New Meridian, in coordination with multiple states and vendors, developed an alternate form of the summative assessment to…
Descriptors: Language Arts, Literacy Education, Mathematics Education, Summative Evaluation
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Bartolucci, Francesco; Pennoni, Fulvia; Vittadini, Giorgio – Journal of Educational and Behavioral Statistics, 2011
An extension of the latent Markov Rasch model is described for the analysis of binary longitudinal data with covariates when subjects are collected in clusters, such as students clustered in classes. For each subject, a latent process is used to represent the characteristic of interest (e.g., ability) conditional on the effect of the cluster to…
Descriptors: Markov Processes, Data Analysis, Maximum Likelihood Statistics, Computation
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Ingels, Steven J.; Pratt, Daniel J.; Herget, Deborah R.; Dever, Jill A.; Fritch, Laura Burns; Ottem, Randolph; Rogers, James E.; Kitmitto, Sami; Leinwand, Steve – National Center for Education Statistics, 2013
This manual has been produced to familiarize data users with the design, and the procedures followed for data collection and processing, in the base year and first follow-up of the High School Longitudinal Study of 2009 (HSLS:09), with emphasis on the first follow-up. It also provides the necessary documentation for use of the public-use data…
Descriptors: High School Students, Longitudinal Studies, Annual Reports, Followup Studies
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Ingels, Steven J.; Pratt, Daniel J.; Herget, Deborah R.; Dever, Jill A.; Fritch, Laura Burns; Ottem, Randolph; Rogers, James E.; Kitmitto, Sami; Leinwand, Steve – National Center for Education Statistics, 2013
The manual that accompanies these appendices was produced to familiarize data users with the design, and the procedures followed for data collection and processing, in the base year and first follow-up of the High School Longitudinal Study of 2009 (HSLS:09), with emphasis on the first follow-up. It also provides the necessary documentation for use…
Descriptors: High School Students, Longitudinal Studies, Annual Reports, Followup Studies
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Schurmeier, Kimberly D.; Atwood, Charles H.; Shepler, Carrie G.; Lautenschlager, Gary J. – Journal of Chemical Education, 2010
Five years of longitudinal data for general chemistry student assessments at the University of Georgia have been analyzed using item response theory (IRT). Our analysis indicates that minor changes in question wording on exams can make significant differences in student performance on assessment questions. This analysis encompasses data from over…
Descriptors: Academic Achievement, Item Response Theory, Universities, Chemistry
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Ballou, Dale – National Center on Performance Incentives, 2008
As currently practiced, value-added assessment relies on a strong assumption about the scales used to measure student achievement, namely that these are interval scales, with equal-sized gains at all points on the scale representing the same increment of learning. Many of the metrics in which test results are expressed do not have this property…
Descriptors: Test Items, Intervals, Data Analysis, Item Response Theory
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Andrich, David – Journal of Applied Measurement, 2002
Reflects on the development of the unidimensional Rasch model for ordered categories and the resistance to some of its initially counterintuitive implications, especially that the thresholds that partition the continuum to form the ordered categories can show an empirical problem with the data. (SLD)
Descriptors: Data Analysis, Item Response Theory, Models
Curtis, David D.; Boman, Peter – International Education Journal, 2007
By using the Rasch model, much detailed diagnostic information is available to developers of survey and assessment instruments and to the researchers who use them. We outline an approach to the analysis of data obtained from the administration of survey instruments that can enable researchers to recognise and diagnose difficulties with those…
Descriptors: Item Response Theory, Data Analysis, Surveys, Questionnaires
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