2004•Journal of Educational MeasurementRequires access

The Relationship Between Item Parameters and Item Fit

Hamzeh Mohd Dodeen

Open publisher page 25 citations

Abstract

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. The item fit was estimated using two fit statistics: the likelihood ratio statistic (X2B), and the standardized residuals (SRs). All the item parameters were simulated to be normally distributed. Results showed that the levels of item discrimination and guessing affected the item‐fit values. As the level of item discrimination or guessing increased, item‐fit values increased and more items misfit the model. The level of item difficulty did not affect the item‐fit statistic.

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What this paper is about

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. The item fit was estimated using two fit statistics: the likelihood ratio statistic (X2B), and the standardized residuals (SRs). All the item parameters were simulated to be normally distributed. Results showed that the levels of item discrimination and guessing affected the item‐fit values. As the level of item discrimination or guessing increased, item‐fit values increased and more items misfit the model. The level of item difficulty did not affect the item‐fit statistic.

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Available abstract

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. The item fit was estimated using two fit statistics: the likelihood ratio statistic (X2B), and the standardized residuals (SRs). All the item parameters were simulated to be normally distributed. Results showed that the levels of item discrimination and guessing affected the item‐fit values. As the level of item discrimination or guessing increased, item‐fit values increased and more items misfit the model. The level of item difficulty did not affect the item‐fit statistic.

Key concepts: Statistic, Statistics, Item response theory, Item analysis, Psychology, Goodness of fit, Differential item functioning, Polytomous Rasch model

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