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Decision rules based on hypothesis tests and effect sizes for logistic regression differential item functioning Gesicki, Adam
Abstract
Logistic Regression (LR) has been a technique used for the detection of items exhibiting differential item functioning (DIF). When it was introduced in 1990, the LR was conceptualized as strictly a test of statistical significance. This led to the over-identification of items as DIF, generally not exhibiting practically (psychometrically) significant differences. The use of blended decision rules – where effect sizes are used in addition to statistical significance in the decision-making process – was proposed to address this issue. Previous work in the literature attempted to align a decision rule grounded in the Mantel-Haenszel (M-H) technique to LR. However, this work is unable to replicate previously recommended cut-offs, through the use of the same methodology on a different data set. It is possible that cut-off values may be dataset specific, which also opens the question of whether universal cut-off values for effect sizes for DIF are a realistic expectation.
Item Metadata
Title |
Decision rules based on hypothesis tests and effect sizes for logistic regression differential item functioning
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
2015
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Description |
Logistic Regression (LR) has been a technique used for the detection of items exhibiting differential item functioning (DIF). When it was introduced in 1990, the LR was conceptualized as strictly a test of statistical significance. This led to the over-identification of items as DIF, generally not exhibiting practically (psychometrically) significant differences. The use of blended decision rules – where effect sizes are used in addition to statistical significance in the decision-making process – was proposed to address this issue. Previous work in the literature attempted to align a decision rule grounded in the Mantel-Haenszel (M-H) technique to LR. However, this work is unable to replicate previously recommended cut-offs, through the use of the same methodology on a different data set. It is possible that cut-off values may be dataset specific, which also opens the question of whether universal cut-off values for effect sizes for DIF are a realistic expectation.
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Genre | |
Type | |
Language |
eng
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Date Available |
2015-10-24
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Provider |
Vancouver : University of British Columbia Library
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Rights |
Attribution-NonCommercial-NoDerivs 2.5 Canada
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DOI |
10.14288/1.0165814
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
2015-11
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Campus | |
Scholarly Level |
Graduate
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Rights URI | |
Aggregated Source Repository |
DSpace
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Item Citations and Data
Rights
Attribution-NonCommercial-NoDerivs 2.5 Canada