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A Comparison of Response Time Threshold Scoring Procedures in Mitigating Bias From Rapid Guessing Behavior
1University of Minnesota Twin Cities, Minneapolis, USA.
Educational and Psychological Measurement
|June 20, 2024
Summary
Rapid guessing (RG), a non-effortful response pattern, can skew test results. Recoding RG responses as missing and using a unidimensional IRT model appears most effective for accurate parameter recovery.
Area of Science:
- Psychometrics
- Educational Measurement
- Cognitive Psychology
Background:
- Rapid guessing (RG) involves short response latencies and non-effortful responding.
- RG can introduce construct-irrelevant variance, biasing measurement properties and scores.
- Existing scoring procedures aim to mitigate RG effects by recoding responses before IRT analysis.
Purpose of the Study:
- To compare the accuracy of four scoring procedures for handling rapid guessing (RG).
- To evaluate parameter recovery under varying conditions of RG misclassification.
- To identify optimal strategies for mitigating the impact of RG in psychometric modeling.
Main Methods:
- A simulation study was conducted to compare four RG scoring procedures.
- Key manipulations included sample size, RG propensity-ability relationship, RG percentage, and misclassification rates.
- Item and ability parameter recovery were assessed using unidimensional and multidimensional IRT models.
Main Results:
- Treating RG responses as incorrect resulted in the highest systematic and random error.
- When RG was perfectly identified, most methods showed similar parameter recovery accuracy.
- Multidimensional IRT models exhibited increased error with higher RG misclassification rates.
Conclusions:
- Recoding rapid guessing (RG) responses as missing is a robust strategy.
- Employing a unidimensional IRT model following recoding offers promising accuracy.
- Careful consideration of RG misclassification is crucial for accurate psychometric analysis.
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