Detecting Aberrant Responding on Unidimensional Pairwise Preference Tests: An Application of I-z Based on the Zinnes-Griggs Ideal Point IRT Model

作者：Lee Philseok^*; Stark Stephen; Chernyshenko Oleksandr S

来源：Applied Psychological Measurement, 2014, 38(5): 391-403.

DOI：10.1177/0146621614526636

• person fit
• appropriateness measurement
• I-z
• pairwise preference
• ideal point
• item response theory (IRT)
• noncognitive assessment
• aberrance
• faking
• random responding

This study investigated the efficacy of the I-z person fit statistic for detecting aberrant responding with unidimensional pairwise preference (UPP) measures, constructed and scored based on the Zinnes-Griggs item response theory (IRT) model, which has been used for a variety of recent noncognitive testing applications. Because UPP measures are used to collect both "self-'' and "other'' reports, the capability of I-z to detect two of the most common and potentially detrimental response sets, namely fake good and random responding, was explored. The effectiveness of I-z was studied using empirical and theoretical critical values for classification, along with test length, test information, the type of statement parameters, and the percentage of items answered aberrantly (20%, 50%, 100%). It was found that I-z was ineffective in detecting fake good responding, with power approaching zero in the 100% aberrance conditions. However, I-z was highly effective in detecting random responding, with power approaching 1.0 in long-test, high information conditions, and there was no diminution in efficacy when using marginal maximum likelihood estimates of statement parameters in place of the true values. Although using empirical critical values for classification provided slightly higher power and more accurate Type I error rates, theoretical critical values, corresponding to a standard normal distribution, provided nearly as good results.

• 出版日期2014-7
• 单位南阳理工学院