Advancing and Evaluating IRT Model Data Fit Indices in Organizational Research
评估了多种IRT模型拟合指标在检测主导型和理想点模型中的表现，发现部分指标更有效，但所有指标均无法准确检测多维性导致的失拟，对组织研究者选择模型有参考价值。
Item response theory (IRT) models have a number of advantages for developing and evaluating scales in organizational research. However, these advantages can be obtained only when the IRT model used to estimate the parameters fits the data well. Therefore, examining IRT model fit is important before drawing conclusions from the data. To test model fit, a wide range of indices are available in the IRT literature and have demonstrated utility in past research. Nevertheless, the performance of many of these indices for detecting misfit has not been directly compared in simulations. The current study evaluates a number of these indices to determine their utility for detecting various types of misfit in both dominance and ideal point IRT models. Results indicate that some indices are more effective than others but that none of the indices accurately detected misfit due to multidimensionality in the data. The implications of these results for future organizational research are discussed.