Results 261 to 270 of about 3,275,659 (305)

Predictive Fit Metrics for Item Response Models

Applied Psychological Measurement, 2022
The fit of an item response model is typically conceptualized as whether a given model could have generated the data. In this study, for an alternative view of fit, “predictive fit,” based on the model’s ability to predict new data is advocated. The authors define two prediction tasks: “missing responses prediction”—where the goal is to predict an in ...
Benjamin A. Stenhaug, Benjamin W. Domingue   +1 more
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Item Analysis: Methods for Fitting the Right Items to the Right Test

2021
When developing a test, there are numerous procedures that are useful for assessing the quality and measurement characteristics of test items. Not all procedures are appropriate for all types of tests, and not all procedures will indicate the same level of quality about a particular item.
Cecil R. Reynolds, Robert A. Altmann, Daniel N. Allen   +2 more
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Goodness of Fit in Item Response Models

Multivariate Behavioral Research, 1995
It is shown that goodness-of-fit criteria developed for the evaluation of multivariate structural models can be applied to assist in evaluating the dimensionality of a test consisting of binary items, and correlative methods regularly employed in factor analysis can be used to diagnose causes of misfit.
R P, McDonald, M M, Mok
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Evaluating Item Fit for Multidimensional Item Response Models

Educational and Psychological Measurement, 2007
This research examines the utility of the s - χ 2 statistic proposed by Orlando and Thissen (2000) in evaluating item fit for multidimensional item response models. Monte Carlo simulation was conducted to investigate both the Type I error and statistical power of this fit statistic in ...
null Bo Zhang, Clement A. Stone
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Assessing item fit: A comparative study of frequentist and Bayesian frameworks

Measurement, 2016
Goodness of fit for item response theory (IRT) models in a frequentist and Bayesian framework are evaluated. The assumptions that are targeted are differential item functioning (DIF), local independence (LI), and the form of the item characteristics curve (ICC) in the one-, two-, and three parameter logistic models.
Khalid, Muhammad Naveed, Glas, Cees A.W.
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Discrepancy measures for item fit analysis in item response theory

Journal of Statistical Computation and Simulation, 2011
Item response theory (IRT) models are commonly used in educational and psychological testing to assess the (latent) ability of examinees and the effectiveness of the test items in measuring this underlying trait. The focus of this paper is on the assessment of item fit for unidimensional IRT models for dichotomous items using a Bayesian method.
S. G. Toribio, J. H. Albert
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All the items fit to print

Communications of the ACM, 2013
3D printing has come of age. It promises to revolutionize a wide range of industries and profoundly change the way people buy and consume.
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The Relationship Between Item Parameters and Item Fit

Journal of Educational Measurement, 2004
The effect of item parameters (discrimination, difficulty, and level of guessing) on the item‐fit statistic was investigated using simulated dichotomous data. Nine tests were simulated using 1,000 persons, 50 items, three levels of item discrimination, three levels of item difficulty, and three levels of guessing.
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A Further Look at the Correlation Between Item Parameters and Item Fit Statistics

Journal of Educational Measurement, 2008
Dodeen (2004) studied the correlation between the item parameters of the three‐parameter logistic model and two item fit statistics, and found some linear relationships (e.g., a positive correlation between item discrimination parameters and item fit statistics) that have the potential for influencing the work of practitioners who employ item response
Sandip Sinharay, Ying Lu
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Bayesian item fit analysis for unidimensional item response theory models

British Journal of Mathematical and Statistical Psychology, 2006
Assessing item fit for unidimensional item response theory models for dichotomous items has always been an issue of enormous interest, but there exists no unanimously agreed item fit diagnostic for these models, and hence there is room for further investigation of the area. This paper employs the posterior predictive model‐checking
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