ERIC ED410241: Quantifying Item Dependency by Fisher’s pdf

ERIC ED410241: Quantifying Item Dependency by Fisher’s

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Three aspects of the usual approach to assessing local item dependency, Yen’s “Q” (H. Huynh, H. Michaels, and S. Ferrara, 1995), deserve further investigation. Pearson correlation coefficients do not distribute normally when the coefficients are large, and thus cannot quantify the dependency well. In the second place, the accuracy of item response theory person ability estimates is always relative to the standard error of the estimation, and in the third place, Yen’s approach does not have a criterion to determine the significance level of the index of dependency between a pair of items (Q3). This paper addresses these concerns by proposing Fisher’s “Z” as the index for item dependency. It compares the statistical properties of Fisher’s Z with Yen’s Q and weights the observed residuals by the standard error of person ability. Items for the study were from the second administration of part of a national medical licensing examination in 1995 taken by 361 first-time test takers.

Fisher’s Z accurately estimated the zero mean dependency for stand-alone items and successfully differentiated stand-alone items from clustered items based on the degree of dependency. This suggests that Fisher’s Z is a valid, reliable, and sensitive index for quantifying item dependency. Two appendixes provide a sample of stand-alone items and a sample of item cluster. (Contains four figures and three references.) (SLD

• Creator/s: ERIC
• Date: 1997-03
• Year: 1997
• Book Topics/Themes: ERIC Archive, Ability, Estimation (Mathematics), Item Response Theory, Reliability, Statistical Analysis, Test Items, Validity, Shen, Linjun

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