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多元二项式拉斯克模型的对数线性表示。

Loglinear representations of multivariate Bernoulli Rasch models.

机构信息

Utrecht University, The Netherlands.

出版信息

Br J Math Stat Psychol. 2011 May;64(Pt 2):337-54. doi: 10.1348/2044-8317.002000. Epub 2010 Dec 7.

Abstract

In this paper, the extended Rasch model for dichotomously scored items is derived from the general multivariate Bernoulli distribution. The necessary and sufficient conditions for the multivariate Bernoulli distribution to be equal to the extended Rasch model provide a new loglinear representation of the extended Rasch model. Conditions are also given under which the extended Rasch model is equal to the random effects Rasch model, and it is shown under what conditions the extended Rasch model is equal to a random effects Rasch model in which the underlying variable has a normal distribution. In addition, alternative models for the construction of likelihood ratio tests are proposed. One of these alternative models is Haberman's extended interaction model. Furthermore, it is shown how both the SPSS and SAS programs can be used to estimate and test loglinear representations of extended Rasch models.

摘要

本文从多维 Bernoulli 分布推导出二项式计分项目的扩展 Rasch 模型。多维 Bernoulli 分布等于扩展 Rasch 模型的必要和充分条件为扩展 Rasch 模型提供了新的对数线性表示。还给出了扩展 Rasch 模型等于随机效应 Rasch 模型的条件,并说明了在什么条件下扩展 Rasch 模型等于具有正态分布的底层变量的随机效应 Rasch 模型。此外,还提出了用于构建似然比检验的替代模型。其中一种替代模型是 Haberman 的扩展交互模型。此外,还展示了如何使用 SPSS 和 SAS 程序来估计和检验扩展 Rasch 模型的对数线性表示。

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