RESEARCH LIBRARY

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.
 

Educational Assessment

This study proposes four indices to quantify item influence and distinguishes them from other available item and test measures. We use simulation methods to evaluate and provide guidelines for interpreting each index, followed by a real data application to illustrate their use in practice. We discuss theoretical considerations regarding when influence presents a psychometric concern and other practical concerns such as how the indices function when reducing influence imbalance.

Handbook of Automated Scoring

In this chapter we describe the historical background that led to development of the simulations and the subsequent refinement of the construct that occurred as the interface was being developed. We then describe the evolution of the automated scoring procedures from linear regression modeling to rule-based procedures.