论文标题

一个概率树模型,用于分析模糊评级数据

A probabilistic tree model to analyze fuzzy rating data

论文作者

Calcagnì, Antonio, Lombardi, Luigi

论文摘要

在此贡献中,我们为在心理测量模型中对模糊评级响应进行建模的问题提供了初步发现。特别是,我们研究了一个概率树模型,目的是表示直接模糊等级量表的阶段机理。采用多项式模型,再加上二项式分布的混合物来对LR型模糊响应的参数进行建模,而二进制决策树则用于阶段的评级机制。参数估计是通过边际最大似然方法进行的,而所提出模型的特征是通过应用于真实数据集的。

In this contribution we provide initial findings to the problem of modeling fuzzy rating responses in a psychometric modeling context. In particular, we study a probabilistic tree model with the aim of representing the stage-wise mechanisms of direct fuzzy rating scales. A Multinomial model coupled with a mixture of Binomial distributions is adopted to model the parameters of LR-type fuzzy responses whereas a binary decision tree is used for the stage-wise rating mechanism. Parameter estimation is performed via marginal maximum likelihood approach whereas the characteristics of the proposed model are evaluated by means of an application to a real dataset.

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