General mixture item response models with different item response structures: Exposition with an application to Likert scales.

General mixture item response models with different item response structures: Exposition with an application to Likert scales.
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具有不同项目响应结构的一般混合物项目响应模型:具有李克特量表的应用。

DOI:
10.3758/s13428-017-0997-0
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发表时间:
2018-12
影响因子:
5.4
通讯作者:
Jeon M
Jeon M
中科院分区:
心理学2区
文献类型:
--
作者:
Tijmstra J;Bolsinova M;Jeon M

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本文提出了一个通用的混合项目反应理论 (IRT) 框架,该框架允许不同类别的人在项目反应背后的过程类型方面存在差异。通过使用混合模型,可以为不同的类别估计具有不同结构的非嵌套IRT模型,并且可以为样本中的每个人估计类别成员资格。如果研究人员能够提供竞争性的测量模型,这种混合 IRT 框架可能会帮助他们处理一些违反测量不变性的问题。为了说明这种方法,我们考虑一个二类混合模型,其中一个人对包含中性中间类别的李克特量表项目的反应要么使用广义部分信用模型建模,要么通过 IRTree 模型建模。在第一个模型中,中间类别(“既不同意也不不同意”)被认为在质量上与其他类别相似,并被认为提供有关该人的认可的信息。在第二个模型中,中间类别被认为是定性的不同并反映了不响应选择,它是使用捕获一个人响应意愿的附加潜在变量进行建模的。通过模拟研究对混合模型进行了研究,并将其应用于实证示例。本文的在线版本 (10.3758/s13428-017-0997-0) 包含补充材料,可供授权用户使用。
This article proposes a general mixture item response theory (IRT) framework that allows for classes of persons to differ with respect to the type of processes underlying the item responses. Through the use of mixture models, nonnested IRT models with different structures can be estimated for different classes, and class membership can be estimated for each person in the sample. If researchers are able to provide competing measurement models, this mixture IRT framework may help them deal with some violations of measurement invariance. To illustrate this approach, we consider a two-class mixture model, where a person’s responses to Likert-scale items containing a neutral middle category are either modeled using a generalized partial credit model, or through an IRTree model. In the first model, the middle category (“neither agree nor disagree”) is taken to be qualitatively similar to the other categories, and is taken to provide information about the person’s endorsement. In the second model, the middle category is taken to be qualitatively different and to reflect a nonresponse choice, which is modeled using an additional latent variable that captures a person’s willingness to respond. The mixture model is studied using simulation studies and is applied to an empirical example. The online version of this article (10.3758/s13428-017-0997-0) contains supplementary material, which is available to authorized users.
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