Embretson Susan E, Yang Xiangdong
School of Psychology, Georgia Institute of Technology, 654 Cherry St., Atlanta, GA 30332-0170, USA.
J Appl Meas. 2006;7(3):335-50.
Contemporary views on cognitive theory (e.g., Sternberg and Perez, 2005) regard typical measurement tasks, such as ability and achievement test items, multidimensional, rather than unidimensional. Assessing the levels and the sources of multidimensionality in an item domain is important for item selection as well as for item revision and development. In this paper, multicomponent latent trait models (MLTM) and traditional multidimensional item response theory models are described mathematically and compared for the nature of the dimensions that can be estimated. Then, some applications are presented to provide examples of MLTM. Last, practical estimation procedures are described, along with syntax, for the estimation of MLTM and a related model.
当代认知理论观点（例如，斯滕伯格和佩雷斯，2005年）认为，诸如能力和成就测试项目等典型测量任务是多维的，而非单维的。评估项目领域中多维性的水平和来源对于项目选择以及项目修订与开发都很重要。本文从数学角度描述了多成分潜在特质模型（MLTM）和传统多维项目反应理论模型，并比较了它们可估计维度的性质。然后，给出了一些应用实例以说明MLTM。最后，描述了MLTM及相关模型估计的实际程序以及语法。
