ERIC Number: EJ808342
Record Type: Journal
Publication Date: 2008
Pages: 21
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-0022-0655
EISSN: N/A
Estimation of Item Response Theory Parameters in the Presence of Missing Data
Finch, Holmes
Journal of Educational Measurement, v45 n3 p225-245 Fall 2008
Missing data are a common problem in a variety of measurement settings, including responses to items on both cognitive and affective assessments. Researchers have shown that such missing data may create problems in the estimation of item difficulty parameters in the Item Response Theory (IRT) context, particularly if they are ignored. At the same time, a number of data imputation methods have been developed outside of the IRT framework and been shown to be effective tools for dealing with missing data. The current study takes several of these methods that have been found to be useful in other contexts and investigates their performance with IRT data that contain missing values. Through a simulation study, it is shown that these methods exhibit varying degrees of effectiveness in terms of imputing data that in turn produce accurate sample estimates of item difficulty and discrimination parameters.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: Researchers
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A