A nonlinear mixed model framework for item response theory
A nonlinear mixed model framework for item response theory
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DOI：
10.1037/1082-989x.8.2.185
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发表时间：
2003-06-01
影响因子：
7
通讯作者：
Kuppens, P
中科院分区：
文献类型：
--
作者：
Rijmen, F;Tuerlinckx, F;Kuppens, P
混合模型通过引入一个或多个随机效应来考虑基于同一聚类的观测值之间的依赖性。共同项目反应理论（IRT）模型引入潜在人变量来模拟同一被试的反应之间的依赖性。假设潜在变量的分布，这些IRT模型在形式上等同于非线性混合模型。它显示了各种IRT模型如何可以表述为非线性混合模型的特定实例。统一框架提供的优势是，不同IRT模型之间的关系变得明确，并且可以相当直接地看到如何适应和扩展现有的IRT模型。一项关于愤怒的自我报告研究说明了这种方法。
Mixed models take the dependency between observations based on the same cluster into account by introducing 1 or more random effects. Common item response theory (IRT) models introduce latent person variables to model the dependence between responses of the same participant. Assuming a distribution for the latent variables, these IRT models are formally equivalent with nonlinear mixed models. It is shown how a variety of IRT models can be formulated as particular instances of nonlinear mixed models. The unifying framework offers the advantage that relations between different IRT models become explicit and that it is rather straightforward to see how existing IRT models can be adapted and extended. The approach is illustrated with a self-report study on anger.