Showing 1 - 2 of 2 Research Library Publications

Detecting Item Parameter Drift in Small Sample Rasch Equating

Posted: | Daniel Jurich, Chunyan Liu

Applied Measurement Education: Volume 36, Issue 4, Pages 326-339

 

This study examines strategies for detecting parameter drift in small-sample equating, crucial for maintaining score comparability in high-stakes exams. Results suggest that methods like mINFIT, mOUTFIT, and Robust-z effectively mitigate drifting anchor items' effects, while caution is advised with the Logit Difference approach. Recommendations are provided for practitioners to manage item parameter drift in small-sample settings.
 

Category:Assessment-Oriented Research, Reliability/Validity, Scoring

Application of Sampling Variance of Item Response Theory Parameter Estimates in Detecting Outliers in Common Item Equating

Posted: | Chunyan Liu, Daniel Jurich

Applied Psychological Measurement: Volume 46, issue 6, page(s) 529-547

 

The current simulation study demonstrated that the sampling variance associated with the item response theory (IRT) item parameter estimates can help detect outliers in the common items under the 2-PL and 3-PL IRT models. The results showed the proposed sampling variance statistic (SV) outperformed the traditional displacement method with cutoff values of 0.3 and 0.5 along a variety of evaluation criteria.

Category:Assessment-Oriented Research, General Measurement