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验证性因素分析与多维拉施模型用于探究考试动机维度的比较

A comparison of confirmatory factor analysis and multidimensional Rasch models to investigate the dimensionality of test-taking motivation.

作者信息

Demars Christine E

机构信息

Center for Assessment and Research Studies, MSC 6806, James Madison University, Harrisonburg, VA 22807, USA.

出版信息

J Appl Meas. 2013;14(2):179-96.

Abstract

Using a scale of test-taking motivation designed to have multiple factors, results are compared from a confirmatory factor analysis (CFA) using LISREL and a multidimensional Rasch partial credit model using ConQuest. Both types of analyses work with latent factors and allow the comparison of nested models. CFA models most typically model a linear relationship between observed and latent variables, while Rasch models specify a non-linear relationship between observed and latent variables. The CFA software provides many more measures of overall fit than ConQuest, which is focused more on the fit of individual items. Despite the conceptual differences in these techniques, the results were similar. The data fit a three-dimensional model better than the one-dimensional or two-dimensional models also hypothesized, although some misfit remained.

摘要

使用一个旨在包含多个因素的考试动机量表,比较了使用LISREL进行的验证性因素分析(CFA)和使用ConQuest进行的多维Rasch部分计分模型的结果。这两种分析类型都处理潜在因素,并允许对嵌套模型进行比较。CFA模型最典型地对观测变量和潜在变量之间的线性关系进行建模,而Rasch模型则指定观测变量和潜在变量之间的非线性关系。CFA软件提供的整体拟合度测量比ConQuest更多,ConQuest更关注单个项目的拟合。尽管这些技术在概念上存在差异,但结果相似。数据与三维模型的拟合优于同样假设的一维或二维模型,尽管仍存在一些拟合不佳的情况。

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