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.
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Armstrong, Ronald D.; Stoumbos, Zachary G.; T., Kung Mabel; and Shi, Min
"On the Performance of the lZ Person-Fit Statistic,"
Practical Assessment, Research, and Evaluation: Vol. 12
, Article 16.
Available at: https://scholarworks.umass.edu/pare/vol12/iss1/16