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Using Fixed Thresholds with Grouped Data in Structural Equation Modeling

机译:在结构方程模型中使用固定阈值和分组数据

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摘要

Valuable methods have been developed for incorporating ordinal variables into structural equation models using a latent response variable formulation. However, some model parameters, such as the means and variances of latent factors, can be quite difficult to interpret because the latent response variables have an arbitrary metric. This limitation can be particularly problematic in growth models, where the means and variances of the latent growth parameters typically have important substantive meaning when continuous measures are used. However, these methods are often applied to grouped data, where the ordered categories actually represent an interval-level variable that has been mea-sured on an ordinal scale for convenience. The method illustrated in this article shows how category threshold values can be incorporated into the model so that interpretation is more meaningful, with particular emphasis given to the application of this technique with latent growth models.
机译:已经开发出使用潜在响应变量公式将有序变量合并到结构方程模型中的有价值的方法。但是,由于潜在响应变量具有任意度量,因此某些模型参数(例如潜在因子的均值和方差)可能很难解释。这种限制在增长模型中尤其成问题,在这种模型中,当使用连续度量时,潜在增长参数的均值和方差通常具有重要的实质意义。但是,这些方法通常应用于分组数据,其中排序的类别实际上代表一个区间级别的变量,为方便起见,该变量已按序数进行了测量。本文说明的方法显示了如何将类别阈值合并到模型中,从而使解释更有意义,并特别强调了该技术与潜在增长模型的应用。

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  • 来源
    《Structural equation modeling》 |2010年第4期|p.590-604|共15页
  • 作者单位

    Educational Psychology and Special Education, Wham Building, Room 223, Mail Code 4618, Southern Illinois University, 635 Wham Drive, Carbondale, IL 62901, USA;

    University of Maryland, College Park;

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