Stephen Humphry, Graduate School of Education, The University of Western Australia, 35 Stirling Highway, Crawley, WA 6009, Australia,
J Appl Meas. 2020;21(4):379-399.
Residual-based fit statistics are among the most common indicators of fit to the Rasch model. There is considerable discussion in the literature of the efficacy of item fit statistics in detecting measurement disturbances. However, to date there has been no investigation of whether these fit statistics are robust to interactions between item discrimination and item difficulty. This study uses simulations to investigate whether interaction effects occur for fit statistics commonly used with the Rasch model. It is found that when the parameters are estimated with the Rasch model, the values of certain item fit statistics vary depending on the interaction between location and discrimination. Specifically, in the study, OUTFIT MNSQ and INFIT MNSQ provide a relatively consistent index of item discrimination across a range of item difficulties, whereas the t-statistic and the log transformed fit residual vary in a systematic fashion that depends on item location.
基于残差的拟合统计量是最常用于评估 Rasch 模型拟合度的指标之一。文献中对项目拟合统计量在检测测量干扰方面的有效性进行了大量讨论。然而，迄今为止，还没有研究这些拟合统计量是否对项目区分度和项目难度之间的相互作用具有稳健性。本研究使用模拟来调查常用的 Rasch 模型拟合统计量是否存在相互作用效应。研究发现，当使用 Rasch 模型估计参数时，某些项目拟合统计量的值会因位置和区分度之间的相互作用而发生变化。具体来说，在本研究中，OUTFIT MNSQ 和 INFIT MNSQ 在一系列项目难度下为项目区分度提供了相对一致的指标，而 t 统计量和对数变换的拟合残差则以依赖于项目位置的系统方式变化。
