Analysis of Distractor Difficulty in Multiple-Choice Items

Two psychometric models are presented for evaluating the difficulty of the distractors in multiple-choice items. They are based on the criterion of rising distractor selection ratios, which facilitates interpretation of the subject and item parameters. Statistical inferential tools are developed in...

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Bibliographic Details
Published inPsychometrika Vol. 69; no. 2; pp. 217 - 234
Main Author Revuelta, Javier
Format Journal Article
LanguageEnglish
Published Heidelberg Springer 01.06.2004
Subjects
Bayesian Statistics
Biological and medical sciences
Difficulty Level
Fundamental and applied biological sciences. Psychology
Item Response Theory
Item Sampling
Multiple Choice Tests
Psychology. Psychoanalysis. Psychiatry
Psychology. Psychophysiology
Psychometrics
Psychometrics. Statistics. Methodology
Statistical Inference
Statistics. Mathematics
Test Items
Human
Statistical analysis
Questionnaire
Item response theory
Psychometrics
item-response models
multiple-choice items
Distractor
MCMC simulation
Test difficulty
Multiple choice
Posterior Predictive Checks
EM algorithm
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Summary:Two psychometric models are presented for evaluating the difficulty of the distractors in multiple-choice items. They are based on the criterion of rising distractor selection ratios, which facilitates interpretation of the subject and item parameters. Statistical inferential tools are developed in a Bayesian framework: modal a posteriori estimation by application of an EM algorithm and model evaluation by monitoring posterior predictive replications of the data matrix. An educational example with real data is included to exemplify the application of the models and compare them with the nominal categories model.
ISSN:0033-3123
1860-0980
DOI:10.1007/BF02295941