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

A Comparison of Strategies for Smoothing Parameter Selection for Mixed-Format Tests Under the Random Groups Design

Posted: | C. Liu, M. J. Kolen

Journal of Educational Measurement: Volume 55, Issue 4, Pages 564-581

 

Smoothing techniques are designed to improve the accuracy of equating functions. The main purpose of this study is to compare seven model selection strategies for choosing the smoothing parameter (C) for polynomial loglinear presmoothing and one procedure for model selection in cubic spline postsmoothing for mixed‐format pseudo tests under the random groups design.

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