The Rasch model is the most prominent member of the class of latent trait models that are in common use. The main reason is that it can be considered as a measurement model that allows to separate person and item parameters, a feature that is referred to as invariance of comparisons or specific objectivity. It is shown that the property is not an exclusive trait of Rasch type models but is also found in alternative latent trait models. It is distinguished between separability in the theoretical measurement model and empirical separability with empirical separability meaning that parameters can be estimated without reference to the other group of parameters. A new type of pairwise estimator with this property is proposed that can be used also in alternative models. Separability is considered in binary models as well as in polytomous models.
翻译:Rasch模型是常用的潜在特征模型类别中最突出的成员,其主要理由是,它可以被视为一种测量模型,可以将人和物品参数分开,这种参数被称为不作比较或特定客观性的特征,表明该属性并非Rasch类型模型的独有特征,但也可以在其他潜在特征模型中找到,将理论计量模型中的分离性与经验性分离性与经验性分离性区分开来,也就是说,参数可以不参考其他一组参数而加以估计。提出了一种新型的对称估量器,这种属性也可以用于替代模型。在二元模型和多元模型中也考虑了分离性。