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Clemens Draxler; Andreas Kurz; Can Gürer; Jan Philipp Nolte – Journal of Educational and Behavioral Statistics, 2024
A modified and improved inductive inferential approach to evaluate item discriminations in a conditional maximum likelihood and Rasch modeling framework is suggested. The new approach involves the derivation of four hypothesis tests. It implies a linear restriction of the assumed set of probability distributions in the classical approach that…
Descriptors: Inferences, Test Items, Item Analysis, Maximum Likelihood Statistics
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Sengul Avsar, Asiye; Tavsancil, Ezel – Educational Sciences: Theory and Practice, 2017
This study analysed polytomous items' psychometric properties according to nonparametric item response theory (NIRT) models. Thus, simulated datasets--three different test lengths (10, 20 and 30 items), three sample distributions (normal, right and left skewed) and three samples sizes (100, 250 and 500)--were generated by conducting 20…
Descriptors: Test Items, Psychometrics, Nonparametric Statistics, Item Response Theory
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Finch, Holmes; Edwards, Julianne M. – Educational and Psychological Measurement, 2016
Standard approaches for estimating item response theory (IRT) model parameters generally work under the assumption that the latent trait being measured by a set of items follows the normal distribution. Estimation of IRT parameters in the presence of nonnormal latent traits has been shown to generate biased person and item parameter estimates. A…
Descriptors: Item Response Theory, Computation, Nonparametric Statistics, Bayesian Statistics
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Padilla, Miguel A.; Divers, Jasmin – Educational and Psychological Measurement, 2013
The performance of the normal theory bootstrap (NTB), the percentile bootstrap (PB), and the bias-corrected and accelerated (BCa) bootstrap confidence intervals (CIs) for coefficient omega was assessed through a Monte Carlo simulation under conditions not previously investigated. Of particular interests were nonnormal Likert-type and binary items.…
Descriptors: Sampling, Statistical Inference, Computation, Statistical Analysis
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Seo, Dong Gi; Weiss, David J. – Educational and Psychological Measurement, 2013
The usefulness of the l[subscript z] person-fit index was investigated with achievement test data from 20 exams given to more than 3,200 college students. Results for three methods of estimating ? showed that the distributions of l[subscript z] were not consistent with its theoretical distribution, resulting in general overfit to the item response…
Descriptors: Achievement Tests, College Students, Goodness of Fit, Item Response Theory
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Monaco, Malina – 1997
The effects of skewed theta distributions on indices of differential item functioning (DIF) were studied, comparing Mantel Haenszel (N. Mantel and W. Haenszel, 1959) and DFIT (N. S. Raju, W. J. van der Linden, and P. F. Fleer) (noncompensatory DIF). The significance of the study is that in educational and psychological data, the distributions one…
Descriptors: Ability, Estimation (Mathematics), Item Bias, Monte Carlo Methods
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Stone, Clement A. – Journal of Educational Measurement, 2000
Describes a goodness-of-fit statistic that considers the imprecision with which ability is estimated and involves constructing item fit tables based on each examinee's posterior distribution of ability, given the likelihood of the response pattern and an assumed marginal ability distribution. Also describes a Monte Carlo resampling procedure to…
Descriptors: Goodness of Fit, Item Response Theory, Mathematical Models, Monte Carlo Methods
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Mount, Robert E.; Schumacker, Randall E. – Journal of Outcome Measurement, 1998
A Monte Carlo study was conducted using simulated dichotomous data to determine the effects of guessing on Rasch item fit statistics and the Logit Residual Index. Results indicate that no significant differences were found between the mean Rasch item fit statistics for each distribution type as the probability of guessing the correct answer…
Descriptors: Goodness of Fit, Guessing (Tests), Item Response Theory, Monte Carlo Methods
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Fowler, Robert L.; Clingman, Joy M. – Educational and Psychological Measurement, 1992
Monte Carlo techniques are used to examine the power of the "B" statistic of R. L. Brennan (1972) to detect negatively discriminating items drawn from a variety of nonnormal population distributions. A simplified procedure is offered for conducting an item-discrimination analysis on typical classroom objective tests. (SLD)
Descriptors: Classroom Techniques, Elementary Secondary Education, Equations (Mathematics), Item Analysis