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Showing 1 to 15 of 1,253 results Save | Export
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Kim, Kyung Yong – Journal of Educational Measurement, 2020
New items are often evaluated prior to their operational use to obtain item response theory (IRT) item parameter estimates for quality control purposes. Fixed parameter calibration is one linking method that is widely used to estimate parameters for new items and place them on the desired scale. This article provides detailed descriptions of two…
Descriptors: Item Response Theory, Evaluation Methods, Test Items, Simulation
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Castellano, Katherine E.; McCaffrey, Daniel F. – Journal of Educational Measurement, 2020
The residual gain score has been of historical interest, and its percentile rank has been of interest more recently given its close correspondence to the popular Student Growth Percentile. However, these estimators suffer from low accuracy and systematic bias (bias conditional on prior latent achievement). This article explores three…
Descriptors: Accuracy, Student Evaluation, Measurement Techniques, Evaluation Methods
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Kim, Hyung Jin; Brennan, Robert L.; Lee, Won-Chan – Journal of Educational Measurement, 2020
In equating, smoothing techniques are frequently used to diminish sampling error. There are typically two types of smoothing: presmoothing and postsmoothing. For polynomial log-linear presmoothing, an optimum smoothing degree can be determined statistically based on the Akaike information criterion or Chi-square difference criterion. For…
Descriptors: Equated Scores, Sampling, Error of Measurement, Statistical Analysis
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Maeda, Hotaka; Zhang, Bo – Journal of Educational Measurement, 2020
When a response pattern does not fit a selected measurement model, one may resort to robust ability estimation. Two popular robust methods are biweight and Huber weight. So far, research on these methods has been quite limited. This article proposes the maximum a posteriori biweight (BMAP) and Huber weight (HMAP) estimation methods. These methods…
Descriptors: Bayesian Statistics, Robustness (Statistics), Computation, Monte Carlo Methods
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Wang, Chun; Chen, Ping; Jiang, Shengyu – Journal of Educational Measurement, 2020
Many large-scale educational surveys have moved from linear form design to multistage testing (MST) design. One advantage of MST is that it can provide more accurate latent trait [theta] estimates using fewer items than required by linear tests. However, MST generates incomplete response data by design; hence, questions remain as to how to…
Descriptors: Test Construction, Test Items, Adaptive Testing, Maximum Likelihood Statistics
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Castellano, Katherine E.; McCaffrey, Daniel F. – Journal of Educational Measurement, 2020
Testing programs are often interested in using a student growth measure. This article presents analytic derivations of the accuracy of common student growth measures on both the raw scale of the test and the percentile rank scale in terms of the proportional reduction in mean squared error and the squared correlation between the estimator and…
Descriptors: Student Evaluation, Accuracy, Testing, Student Development
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Wu, Qian; De Laet, Tinne; Janssen, Rianne – Journal of Educational Measurement, 2019
Single-best answers to multiple-choice items are commonly dichotomized into correct and incorrect responses, and modeled using either a dichotomous item response theory (IRT) model or a polytomous one if differences among all response options are to be retained. The current study presents an alternative IRT-based modeling approach to…
Descriptors: Multiple Choice Tests, Item Response Theory, Test Items, Responses
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Wind, Stefanie A.; Sebok-Syer, Stefanie S. – Journal of Educational Measurement, 2019
When practitioners use modern measurement models to evaluate rating quality, they commonly examine rater fit statistics that summarize how well each rater's ratings fit the expectations of the measurement model. Essentially, this approach involves examining the unexpected ratings that each misfitting rater assigned (i.e., carrying out analyses of…
Descriptors: Measurement, Models, Evaluators, Simulation
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Man, Kaiwen; Harring, Jeffrey R.; Sinharay, Sandip – Journal of Educational Measurement, 2019
Data mining methods have drawn considerable attention across diverse scientific fields. However, few applications could be found in the areas of psychological and educational measurement, and particularly pertinent to this article, in test security research. In this study, various data mining methods for detecting cheating behaviors on large-scale…
Descriptors: Information Retrieval, Data Analysis, Identification, Tests
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Feuerstahler, Leah; Wilson, Mark – Journal of Educational Measurement, 2019
Scores estimated from multidimensional item response theory (IRT) models are not necessarily comparable across dimensions. In this article, the concept of aligned dimensions is formalized in the context of Rasch models, and two methods are described--delta dimensional alignment (DDA) and logistic regression alignment (LRA)--to transform estimated…
Descriptors: Item Response Theory, Models, Scores, Comparative Analysis
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Zhang, Zhonghua; Zhao, Mingren – Journal of Educational Measurement, 2019
The present study evaluated the multiple imputation method, a procedure that is similar to the one suggested by Li and Lissitz (2004), and compared the performance of this method with that of the bootstrap method and the delta method in obtaining the standard errors for the estimates of the parameter scale transformation coefficients in item…
Descriptors: Item Response Theory, Error Patterns, Item Analysis, Simulation
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Wolkowitz, Amanda A.; Wright, Keith D. – Journal of Educational Measurement, 2019
This article explores the amount of equating error at a passing score when equating scores from exams with small samples sizes. This article focuses on equating using classical test theory methods of Tucker linear, Levine linear, frequency estimation, and chained equipercentile equating. Both simulation and real data studies were used in the…
Descriptors: Error Patterns, Sample Size, Test Theory, Test Bias
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Bergner, Yoav; Choi, Ikkyu; Castellano, Katherine E. – Journal of Educational Measurement, 2019
Allowance for multiple chances to answer constructed response questions is a prevalent feature in computer-based homework and exams. We consider the use of item response theory in the estimation of item characteristics and student ability when multiple attempts are allowed but no explicit penalty is deducted for extra tries. This is common…
Descriptors: Models, Item Response Theory, Homework, Computer Assisted Instruction
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Albano, Anthony D.; Cai, Liuhan; Lease, Erin M.; McConnell, Scott R. – Journal of Educational Measurement, 2019
Studies have shown that item difficulty can vary significantly based on the context of an item within a test form. In particular, item position may be associated with practice and fatigue effects that influence item parameter estimation. The purpose of this research was to examine the relevance of item position specifically for assessments used in…
Descriptors: Test Items, Computer Assisted Testing, Item Analysis, Difficulty Level
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Steedle, Jeffrey T.; Radunzel, Justine; Mattern, Krista D. – Journal of Educational Measurement, 2019
Ensuring postsecondary readiness is a goal of K-12 education, but it is unclear whether high school students should get different messages about the required levels of academic preparation depending on their postsecondary trajectories. This study estimated readiness benchmark scores on a college admissions test predictive of earning good grades in…
Descriptors: College Admission, College Entrance Examinations, College Readiness, High School Students
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