NotesFAQContact Us
Collection
Advanced
Search Tips
Publication Date
In 20250
Since 20240
Since 2021 (last 5 years)0
Since 2016 (last 10 years)0
Since 2006 (last 20 years)11
Audience
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 23 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Kopf, Julia; Zeileis, Achim; Strobl, Carolin – Educational and Psychological Measurement, 2015
Differential item functioning (DIF) indicates the violation of the invariance assumption, for instance, in models based on item response theory (IRT). For item-wise DIF analysis using IRT, a common metric for the item parameters of the groups that are to be compared (e.g., for the reference and the focal group) is necessary. In the Rasch model,…
Descriptors: Test Items, Equated Scores, Test Bias, Item Response Theory
Peer reviewed Peer reviewed
Direct linkDirect link
Seo, Dong Gi; Weiss, David J. – Educational and Psychological Measurement, 2015
Most computerized adaptive tests (CATs) have been studied using the framework of unidimensional item response theory. However, many psychological variables are multidimensional and might benefit from using a multidimensional approach to CATs. This study investigated the accuracy, fidelity, and efficiency of a fully multidimensional CAT algorithm…
Descriptors: Computer Assisted Testing, Adaptive Testing, Accuracy, Fidelity
Peer reviewed Peer reviewed
Direct linkDirect link
Wang, Wen-Chung; Jin, Kuan-Yu; Qiu, Xue-Lan; Wang, Lei – Journal of Educational Measurement, 2012
In some tests, examinees are required to choose a fixed number of items from a set of given items to answer. This practice creates a challenge to standard item response models, because more capable examinees may have an advantage by making wiser choices. In this study, we developed a new class of item response models to account for the choice…
Descriptors: Item Response Theory, Test Items, Selection, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Ghaffarzadegan, Navid; Stewart, Thomas R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2011
Elwin, Juslin, Olsson, and Enkvist (2007) and Henriksson, Elwin, and Juslin (2010) offered the constructivist coding hypothesis to describe how people code the outcomes of their decisions when availability of feedback is conditional on the decision. They provided empirical evidence only for the 0.5 base rate condition. This commentary argues that…
Descriptors: Decision Making, Feedback (Response), Constructivism (Learning), Hypothesis Testing
Peer reviewed Peer reviewed
Direct linkDirect link
Kang, Taehoon; Cohen, Allan S.; Sung, Hyun-Jung – Applied Psychological Measurement, 2009
This study examines the utility of four indices for use in model selection with nested and nonnested polytomous item response theory (IRT) models: a cross-validation index and three information-based indices. Four commonly used polytomous IRT models are considered: the graded response model, the generalized partial credit model, the partial credit…
Descriptors: Item Response Theory, Models, Selection, Simulation
Peer reviewed Peer reviewed
Direct linkDirect link
Moses, Tim; Holland, Paul W. – Journal of Educational Measurement, 2009
In this study, we compared 12 statistical strategies proposed for selecting loglinear models for smoothing univariate test score distributions and for enhancing the stability of equipercentile equating functions. The major focus was on evaluating the effects of the selection strategies on equating function accuracy. Selection strategies' influence…
Descriptors: Equated Scores, Selection, Statistical Analysis, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Feiming; Cohen, Allan S.; Kim, Seock-Ho; Cho, Sun-Joo – Applied Psychological Measurement, 2009
This study examines model selection indices for use with dichotomous mixture item response theory (IRT) models. Five indices are considered: Akaike's information coefficient (AIC), Bayesian information coefficient (BIC), deviance information coefficient (DIC), pseudo-Bayes factor (PsBF), and posterior predictive model checks (PPMC). The five…
Descriptors: Item Response Theory, Models, Selection, Methods
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Moses, Tim; Holland, Paul – ETS Research Report Series, 2008
This study addressed 2 issues of using loglinear models for smoothing univariate test score distributions and for enhancing the stability of equipercentile equating functions. One issue was a comparative assessment of several statistical strategies that have been proposed for selecting 1 from several competing model parameterizations. Another…
Descriptors: Equated Scores, Selection, Models, Statistical Analysis
Peer reviewed Peer reviewed
Direct linkDirect link
Marewski, Julian N.; Schooler, Lael J. – Psychological Review, 2011
How do people select among different strategies to accomplish a given task? Across disciplines, the strategy selection problem represents a major challenge. We propose a quantitative model that predicts how selection emerges through the interplay among strategies, cognitive capacities, and the environment. This interplay carves out for each…
Descriptors: Foreign Countries, Models, Familiarity, Holistic Approach
Peer reviewed Peer reviewed
Olejnik, Stephen; Mills, Jamie; Keselman, Harvey – Journal of Experimental Education, 2000
Evaluated the use of Mallow's C(p) and Wherry's adjusted R squared (R. Wherry, 1931) statistics to select a final model from a pool of model solutions using computer generated data. Neither statistic identified the underlying regression model any better than, and usually less well than, the stepwise selection method, which itself was poor for…
Descriptors: Computer Simulation, Models, Regression (Statistics), Selection
Peer reviewed Peer reviewed
Direct linkDirect link
Woods, Carol M. – Psychological Methods, 2006
Popular methods for fitting unidimensional item response theory (IRT) models to data assume that the latent variable is normally distributed in the population of respondents, but this can be unreasonable for some variables. Ramsay-curve IRT (RC-IRT) was developed to detect and correct for this nonnormality. The primary aims of this article are to…
Descriptors: Item Response Theory, Models, Evaluation Methods, Simulation
Peer reviewed Peer reviewed
Hu, Li-tze; Bentler, Peter M. – Structural Equation Modeling, 1999
The adequacy of "rule of thumb" conventional cutoff criteria and several alternatives for fit indices in covariance structure analysis was evaluated through simulation. Analyses suggest that, for all recommended fit indexes except one, a cutoff criterion greater than (or sometimes smaller than) the conventional rule of thumb is required…
Descriptors: Criteria, Evaluation Methods, Goodness of Fit, Models
Kim, Sung-Ho – 1992
One of the major problems that a tree-approach to data analysis often encounters is the instability of tree-structures. The instability issue must be dealt with before data can be interpreted by this method. Examining instability at a node of a tree provides insight into the instability of the whole tree, because the same theory of instability…
Descriptors: Error of Measurement, Models, Regression (Statistics), Sample Size
Lewis, Charles; Willingham, Warren W. – 1995
As strongly suggested by recent work, patterns of gender difference can change because of changes in the selectivity of the sample itself. This is a statistical influence connected with the distributions of female and male scores, rather than a substantive influence related to demographic characteristics of the sample such as age or ethnicity. It…
Descriptors: Age Differences, Educational Assessment, Models, Sampling
Peer reviewed Peer reviewed
van Onna, M. J. H. – Psychometrika, 2002
Studied whether ordered latent class models can be used as nonparametric item response theory (NIRT) models to scale polytomous models. Simulation findings show that the Bayesian estimation method presented can handle the inequality restrictions on the parameters and the sparseness of the data quite well. (SLD)
Descriptors: Bayesian Statistics, Equations (Mathematics), Estimation (Mathematics), Item Response Theory
Previous Page | Next Page ยป
Pages: 1  |  2