Marais Ida, Andrich David
Graduate School of Education, The University of Western Australia, Mailbox M428, 35 Stirling Highway, Crawley, WA 6009, Australia.
J Appl Meas. 2008;9(3):200-15.
Local independence in the Rasch model can be violated in two generic ways that are generally not distinguished clearly in the literature. In this paper we distinguish between a violation of unidimensionality, which we call trait dependence, and a specific violation of statistical independence, which we call response dependence, both of which violate local independence. Distinct algebraic formulations for trait and response dependence are developed as violations of the dichotomous Rasch model, data are simulated with varying degrees of dependence according to these formulations, and then analysed according to the Rasch model assuming no violations. Relative to the case of no violation it is shown that trait and response dependence result in opposite effects on the unit of scale as manifested in the range and standard deviation of the scale and the standard deviation of person locations. In the case of trait dependence the scale is reduced; in the case of response dependence it is increased. Again, relative to the case of no violation, the two violations also have opposite effects on the person separation index (analogous to Cronbach's alpha reliability index of traditional test theory in value and construction): it decreases for data with trait dependence; it increases for data with response dependence. A standard way of accounting for dependence is to combine the dependent items into a higher-order polytomous item. This typically results in a decreased person separation index index and Cronbach's alpha, compared with analysing items as discrete, independent items. This occurs irrespective of the kind of dependence in the data, and so further contributes to the two violations not being distinguished clearly. In an attempt to begin to distinguish between them statistically this paper articulates the opposite effects of these two violations in the dichotomous Rasch model.
拉施模型中的局部独立性可能会以两种一般方式被违背,而这两种方式在文献中通常没有得到清晰区分。在本文中,我们区分了对单维性的违背(我们称之为特质依赖性)和对统计独立性的一种特定违背(我们称之为反应依赖性),这两种情况都会违背局部独立性。针对特质依赖性和反应依赖性,我们开发了不同的代数公式,将其作为对二分拉施模型的违背情况,根据这些公式模拟出具有不同依赖程度的数据,然后在假设没有违背的情况下按照拉施模型进行分析。相对于没有违背的情况,结果表明特质依赖性和反应依赖性对量表单位产生相反的影响,这体现在量表的范围和标准差以及人员位置的标准差上。在特质依赖性的情况下,量表会缩小;在反应依赖性的情况下,量表会增大。同样,相对于没有违背的情况,这两种违背情况对人员分离指数(类似于传统测试理论中克龙巴赫α信度指数的数值和构建方式)也有相反的影响:对于具有特质依赖性的数据,该指数会降低;对于具有反应依赖性的数据,该指数会升高。一种处理依赖性的标准方法是将相关项目合并为一个高阶多分类项目。与将项目作为离散、独立项目进行分析相比,这通常会导致人员分离指数和克龙巴赫α系数降低。无论数据中依赖性的类型如何,都会出现这种情况,因此这进一步导致这两种违背情况没有得到清晰区分。为了尝试从统计学上开始区分它们,本文阐述了这两种违背情况在二分拉施模型中的相反影响。