Non‐ignorable missingness item response theory models for choice effects in examinee‐selected items

Non‐ignorable missingness item response theory models for choice effects in examinee‐selected items
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考生所选项目选择效应的不可忽略缺失项目反应理论模型

DOI:
10.1111/bmsp.12097
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发表时间:
2017
影响因子:
2.6
通讯作者:
Wen
Wen
中科院分区:
心理学3区
文献类型:
--
作者:
Chen;Wen

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受试者选择项目(ESI)设计,其中要求受试者对给定集合中的固定数量的项目做出响应,总是产生不完整的数据(即,当仅回答所选项目时,其他项目的数据缺失),这些项目在似然性推断中可能是不可验证的。当ESI数据非随机缺失时,标准项目反应理论(IRT)模型变得不可行。为了解决这个问题,作者提出了一个二维的IRT模型,假定一个一维的IRT模型的观察数据和名义选择模式。假设两个潜变量遵循二元正态分布。在本研究中,采用mirt免费软件包估计参数。作者进行了一个实验,以证明ESI数据往往是不可解释的,并确定如何将新模型应用于收集的数据。两个后续的模拟研究进行评估的参数恢复的新模型和参数估计的后果忽略MNAR数据。两个模拟研究的结果表明,新模型的参数恢复良好,参数恢复不良时,不可重复的缺失数据被错误地视为可重复的。
Examinee-selected item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set, always yields incomplete data (i.e., when only the selected items are answered, data are missing for the others) that are likely non-ignorable in likelihood inference. Standard item response theory (IRT) models become infeasible when ESI data are missing not at random (MNAR). To solve this problem, the authors propose a two-dimensional IRT model that posits one unidimensional IRT model for observed data and another for nominal selection patterns. The two latent variables are assumed to follow a bivariate normal distribution. In this study, the mirt freeware package was adopted to estimate parameters. The authors conduct an experiment to demonstrate that ESI data are often non-ignorable and to determine how to apply the new model to the data collected. Two follow-up simulation studies are conducted to assess the parameter recovery of the new model and the consequences for parameter estimation of ignoring MNAR data. The results of the two simulation studies indicate good parameter recovery of the new model and poor parameter recovery when non-ignorable missing data were mistakenly treated as ignorable.
DOI: 10.1177/0013164414561785
发表时间: 2015-10-01
影响因子: 2.7
作者:
Koehler, Carmen;Pohl, Steffi;Carstensen, Claus H.
通讯作者: Carstensen, Claus H.
DOI: 10.1177/0013164413504926
发表时间: 2014-06-01
影响因子: 2.7
作者:
Pohl, Steffi;Graefe, Linda;Rose, Norman
通讯作者: Rose, Norman