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Tang, Xiaodan; Karabatsos, George; Chen, Haiqin – Applied Measurement in Education, 2020
In applications of item response theory (IRT) models, it is known that empirical violations of the local independence (LI) assumption can significantly bias parameter estimates. To address this issue, we propose a threshold-autoregressive item response theory (TAR-IRT) model that additionally accounts for order dependence among the item responses…
Descriptors: Item Response Theory, Test Items, Models, Computation
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Lozano, José H.; Revuelta, Javier – Applied Measurement in Education, 2021
The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…
Descriptors: Bayesian Statistics, Computation, Learning, Testing
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Bjermo, Jonas; Miller, Frank – Applied Measurement in Education, 2021
In recent years, the interest in measuring growth in student ability in various subjects between different grades in school has increased. Therefore, good precision in the estimated growth is of importance. This paper aims to compare estimation methods and test designs when it comes to precision and bias of the estimated growth of mean ability…
Descriptors: Scaling, Ability, Computation, Test Items
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Guo, Hongwen; Rios, Joseph A.; Haberman, Shelby; Liu, Ou Lydia; Wang, Jing; Paek, Insu – Applied Measurement in Education, 2016
Unmotivated test takers using rapid guessing in item responses can affect validity studies and teacher and institution performance evaluation negatively, making it critical to identify these test takers. The authors propose a new nonparametric method for finding response-time thresholds for flagging item responses that result from rapid-guessing…
Descriptors: Guessing (Tests), Reaction Time, Nonparametric Statistics, Models
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Michaelides, Michalis P.; Haertel, Edward H. – Applied Measurement in Education, 2014
The standard error of equating quantifies the variability in the estimation of an equating function. Because common items for deriving equated scores are treated as fixed, the only source of variability typically considered arises from the estimation of common-item parameters from responses of samples of examinees. Use of alternative, equally…
Descriptors: Equated Scores, Test Items, Sampling, Statistical Inference
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Sass, D. A.; Schmitt, T. A.; Walker, C. M. – Applied Measurement in Education, 2008
Item response theory (IRT) procedures have been used extensively to study normal latent trait distributions and have been shown to perform well; however, less is known concerning the performance of IRT with non-normal latent trait distributions. This study investigated the degree of latent trait estimation error under normal and non-normal…
Descriptors: Difficulty Level, Item Response Theory, Test Items, Computation
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Clauser, Brian E.; Harik, Polina; Margolis, Melissa J.; McManus, I. C.; Mollon, Jennifer; Chis, Liliana; Williams, Simon – Applied Measurement in Education, 2009
Numerous studies have compared the Angoff standard-setting procedure to other standard-setting methods, but relatively few studies have evaluated the procedure based on internal criteria. This study uses a generalizability theory framework to evaluate the stability of the estimated cut score. To provide a measure of internal consistency, this…
Descriptors: Generalizability Theory, Group Discussion, Standard Setting (Scoring), Scoring