An Examination of Two Procedures for Identifying Consequential Item Parameter Drift

The purpose of the present study was to develop and evaluate two procedures flagging consequential item parameter drift (IPD) in an operational testing program. The first procedure was based on flagging items that exhibit a meaningful magnitude of IPD using a critical value that was defined to represent barely tolerable IPD. The second procedure was based on flagging items in which the D2 statistic was more than two standard deviations from the mean. Both procedures were implemented using an iterative purification approach to detect IPD. A simulation study was implemented to evaluate the effectiveness of both detection procedures in flagging non-negligible IPD. Both procedures were able to identify IPD and the iterative purification method provided useful information regarding the consequences of excluding or including a flagged item. The advantages and disadvantages of both procedures as well as possible modifications intended to improve the procedures’ effectiveness are discussed in the article.