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Kim, Kyung Yong; Lee, Won-Chan – Applied Measurement in Education, 2017
This article provides a detailed description of three factors (specification of the ability distribution, numerical integration, and frame of reference for the item parameter estimates) that might affect the item parameter estimation of the three-parameter logistic model, and compares five item calibration methods, which are combinations of the…
Descriptors: Test Items, Item Response Theory, Comparative Analysis, Methods
Sachse, Karoline A.; Haag, Nicole – Applied Measurement in Education, 2017
Standard errors computed according to the operational practices of international large-scale assessment studies such as the Programme for International Student Assessment's (PISA) or the Trends in International Mathematics and Science Study (TIMSS) may be biased when cross-national differential item functioning (DIF) and item parameter drift are…
Descriptors: Error of Measurement, Test Bias, International Assessment, Computation
Sinharay, Sandip – Applied Measurement in Education, 2017
Karabatsos compared the power of 36 person-fit statistics using receiver operating characteristics curves and found the "H[superscript T]" statistic to be the most powerful in identifying aberrant examinees. He found three statistics, "C", "MCI", and "U3", to be the next most powerful. These four statistics,…
Descriptors: Nonparametric Statistics, Goodness of Fit, Simulation, Comparative Analysis
Lee, Wooyeol; Cho, Sun-Joo – Applied Measurement in Education, 2017
Utilizing a longitudinal item response model, this study investigated the effect of item parameter drift (IPD) on item parameters and person scores via a Monte Carlo study. Item parameter recovery was investigated for various IPD patterns in terms of bias and root mean-square error (RMSE), and percentage of time the 95% confidence interval covered…
Descriptors: Item Response Theory, Test Items, Bias, Computation
Humphry, Stephen; Heldsinger, Sandra; Andrich, David – Applied Measurement in Education, 2014
One of the best-known methods for setting a benchmark standard on a test is that of Angoff and its modifications. When scored dichotomously, judges estimate the probability that a benchmark student has of answering each item correctly. As in most methods of standard setting, it is assumed implicitly that the unit of the latent scale of the…
Descriptors: Foreign Countries, Standard Setting (Scoring), Judges, Item Response Theory
Ho, Tsung-Han; Dodd, Barbara G. – Applied Measurement in Education, 2012
In this study we compared five item selection procedures using three ability estimation methods in the context of a mixed-format adaptive test based on the generalized partial credit model. The item selection procedures used were maximum posterior weighted information, maximum expected information, maximum posterior weighted Kullback-Leibler…
Descriptors: Computer Assisted Testing, Adaptive Testing, Test Items, Selection
Murphy, Daniel L.; Beretvas, S. Natasha – Applied Measurement in Education, 2015
This study examines the use of cross-classified random effects models (CCrem) and cross-classified multiple membership random effects models (CCMMrem) to model rater bias and estimate teacher effectiveness. Effect estimates are compared using CTT versus item response theory (IRT) scaling methods and three models (i.e., conventional multilevel…
Descriptors: Teacher Effectiveness, Comparative Analysis, Hierarchical Linear Modeling, Test Theory
Puhan, Gautam; Sinharay, Sandip; Haberman, Shelby; Larkin, Kevin – Applied Measurement in Education, 2010
Will subscores provide additional information than what is provided by the total score? Is there a method that can estimate more trustworthy subscores than observed subscores? To answer the first question, this study evaluated whether the true subscore was more accurately predicted by the observed subscore or total score. To answer the second…
Descriptors: Licensing Examinations (Professions), Scores, Computation, Methods
Penfield, Randall D. – Applied Measurement in Education, 2006
This study applied the maximum expected information (MEI) and the maximum posterior-weighted information (MPI) approaches of computer adaptive testing item selection to the case of a test using polytomous items following the partial credit model. The MEI and MPI approaches are described. A simulation study compared the efficiency of ability…
Descriptors: Bayesian Statistics, Adaptive Testing, Computer Assisted Testing, Test Items

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