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Kogar, Esin Yilmaz; Kelecioglu, Hülya – Journal of Education and Learning, 2017
The purpose of this research is to first estimate the item and ability parameters and the standard error values related to those parameters obtained from Unidimensional Item Response Theory (UIRT), bifactor (BIF) and Testlet Response Theory models (TRT) in the tests including testlets, when the number of testlets, number of independent items, and…
Descriptors: Item Response Theory, Models, Mathematics Tests, Test Items
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Schoeneberger, Jason A. – Journal of Experimental Education, 2016
The design of research studies utilizing binary multilevel models must necessarily incorporate knowledge of multiple factors, including estimation method, variance component size, or number of predictors, in addition to sample sizes. This Monte Carlo study examined the performance of random effect binary outcome multilevel models under varying…
Descriptors: Sample Size, Models, Computation, Predictor Variables
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Liang, Tie; Wells, Craig S.; Hambleton, Ronald K. – Journal of Educational Measurement, 2014
As item response theory has been more widely applied, investigating the fit of a parametric model becomes an important part of the measurement process. There is a lack of promising solutions to the detection of model misfit in IRT. Douglas and Cohen introduced a general nonparametric approach, RISE (Root Integrated Squared Error), for detecting…
Descriptors: Item Response Theory, Measurement Techniques, Nonparametric Statistics, Models
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Forero, Carlos G.; Maydeu-Olivares, Alberto – Psychological Methods, 2009
The performance of parameter estimates and standard errors in estimating F. Samejima's graded response model was examined across 324 conditions. Full information maximum likelihood (FIML) was compared with a 3-stage estimator for categorical item factor analysis (CIFA) when the unweighted least squares method was used in CIFA's third stage. CIFA…
Descriptors: Factor Analysis, Least Squares Statistics, Computation, Item Response Theory
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Murphy, Daniel L.; Pituch, Keenan A. – Journal of Experimental Education, 2009
The authors examined the robustness of multilevel linear growth curve modeling to misspecification of an autoregressive moving average process. As previous research has shown (J. Ferron, R. Dailey, & Q. Yi, 2002; O. Kwok, S. G. West, & S. B. Green, 2007; S. Sivo, X. Fan, & L. Witta, 2005), estimates of the fixed effects were unbiased, and Type I…
Descriptors: Sample Size, Computation, Evaluation Methods, Longitudinal Studies
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Wyse, Adam E.; Mapuranga, Raymond – International Journal of Testing, 2009
Differential item functioning (DIF) analysis is a statistical technique used for ensuring the equity and fairness of educational assessments. This study formulates a new DIF analysis method using the information similarity index (ISI). ISI compares item information functions when data fits the Rasch model. Through simulations and an international…
Descriptors: Test Bias, Evaluation Methods, Test Items, Educational Assessment
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Baker, Frank B. – Applied Psychological Measurement, 1993
Using simulation, the effect that misspecification of elements in the weight matrix has on estimates of basic parameters of the linear logistic test model was studied. Results indicate that, because specifying elements of the weight matrix is a subjective process, it must be done with great care. (SLD)
Descriptors: Error Patterns, Estimation (Mathematics), Item Response Theory, Matrices