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A Comprehensive Approach for Assessing Person Fit With Test-Retest Data

机译：用重测数据评估人身健康的综合方法

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摘要

Item response theory (IRT) models allow model-data fit to be assessed at the individual level by using person-fit indices. This assessment is also feasible when IRT is used to model test-retest data. However, person-fit developments for this type of modeling are virtually nonexistent. This article proposes a general person-fit approach for test-retest data, which is based on practical likelihood-based indices. The approach is intended for two types of assumption regarding trait levels—stability and change— and can be used with a variety of IRT models. It consists of two groups of indices: (a) overall indices based on the full test-retest pattern, which are more powerful and are intended to flag a respondent as potentially inconsistent; and (b) partial indices intended to provide additional information about the location and sources of misfit. Furthermore, because the overall procedures assume local independence under repetition, a statistic for assessing the presence of retest effects at the individual level is also proposed. The functioning of the procedures was assessed by using simulation and is illustrated with two empirical studies: a stability study based on gradedresponse items and a change study based on binary items. Finally, limitations and further lines of research are discussed.
机译：项目响应理论（IRT）模型允许通过使用人员适合度指数在个人级别评估模型数据的适合度。当使用IRT对重测数据建模时，这种评估也是可行的。但是，这种类型的建模几乎不存在适合个人的开发。本文提出了一种适用于重测数据的通用人员拟合方法，该方法基于实际的基于似然性的指标。该方法旨在针对性状水平的两种类型的假设（稳定性和变化），并且可以与多种IRT模型一起使用。它由两组指标组成：（a）基于完整的测试-再测试模式的总体指标，功能更强大，旨在标记受访者潜在的不一致; （b）部分索引旨在提供有关失配的位置和来源的其他信息。此外，由于总体程序假定重复下的局部独立性，因此还提出了用于评估个人层面上重测效果是否存在的统计数据。通过模拟评估了程序的功能，并通过两项经验研究进行了说明：基于分级响应项目的稳定性研究和基于二元项目的变更研究。最后，讨论了局限性和进一步的研究方向。

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