Investigating the Impact of Missing Data Handling Methods on the Detection of Differential Item Functioning

Year 2018, Volume: 5 Issue: 1, 1 - 14, 01.01.2018

Hüseyin Selvi , Devrim Özdemir Alıcı

https://doi.org/10.21449/ijate.330885

Cited By: 3

Abstract

In this study, it is aimed to investigate the
impact of different missing data handling methods on the detection of
Differential Item Functioning methods (Mantel Haenszel and Standardization
methods based on Classical Test Theory and Likelihood Ratio Test method based
on Item Response Theory). In this regard, on the data acquired from 1046
candidates who entered to Foreign National Student Exam (FNSE) held in year
2016 by Mersin University (MEU) and answered Basic Skills subtest, using
different missing data handling methods, differential item functioning analyses
with Mantel Haenszel, Standardization and Likelihood Ratio Test methods are
performed. Basic Skills test consists of 80 multiple choice items. The items
are all binary scored (1-0) items. Among the participants 523 are female and
523 are male. The findings showed that the number of items flagged as DIF has
changed with the used missing data handling methods. The DIF detection methods
based on Classical Test Theory are more consistent within themselves compared
to DIF detection method based on Item Response Theory, whereas the used missing
data handling methods differentiate the DIF detected items and this difference
reaches a significant level for Mantel Haenszel method

Keywords

Differential Item Functioning DIF, Test and Item Bias, Missing Values; Imputation of Missing Data, Mantel Haenszel, Likelihood Ratio Test

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