On the Performance of the l_Z Person-Fit Statistic

Authors

Ronald D. Armstrong
Zachary G. Stoumbos
Kung Mabel T.
Min Shi

DOI

https://doi.org/10.7275/xz5d-7j62

Abstract

Person-fit measurement refers to statistical methods used to detect improbable item-score patterns. This study investigates the detection effectiveness of the z l statistic, which is one of the most popular and powerful person-fit statistics in the literature to date. The contributions of the present study are three-fold. First, the simulation results show that the detection power of the z l statistic is largely hinged on test characteristics, particularly the test difficulty. Therefore, the z l statistic should be used with caution in an operational testing environment. Second, this paper provides a clear explanation for the poor performance of the z l statistic under certain situations. The third objective is to present a summary of the patterns and conditions for which the z l statistic is not recommended for the detection of aberrancy. This can be used as a checklist for implementation purposes. Accessed 41,380 times on https://pareonline.net from December 05, 2007 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.

Recommended Citation

Armstrong, Ronald D.; Stoumbos, Zachary G.; T., Kung Mabel; and Shi, Min (2019) "On the Performance of the l_Z Person-Fit Statistic," Practical Assessment, Research, and Evaluation: Vol. 12, Article 16.
DOI: https://doi.org/10.7275/xz5d-7j62
Available at: https://scholarworks.umass.edu/pare/vol12/iss1/16