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Large Type Fit Indices of Mathematics Adult Learners: A Covariance Structure Model

机译:数学成人学习者的大型拟合指数:协方差结构模型

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Fit is the ability of a model to reproduce the data in the variance-covariance matrix form. A good fitting model is one that is reasonably consistent with the data and doesn’t require respecification and also its measurement model is required before estimating paths in a covariance structure model. A baseline model of four constructs together with a combination of none, one, two, three or four additional constructs was constructed with latent variables: educational performance, socio-economic label, self concept and parental authority using dichotomous digits 0 or 1 for each additional construct. We considered 16 progressively nested models starting with baseline model using the mathematics adult learners data from the modeling sample and employing some large fit indexes which are commonly used (NFI, NNFI, CFI, GFI, PGFI, among others) Usluel, et al. (2008) to test the fitness of the model. The measures of model fit based on results from analysis of the covariance structure model are presented Keywords: Fit Indices; Structural Equation Modeling; Bernoulli Digits; Latent Constructs; Educational Performance
机译:拟合是模型以方差-协方差矩阵形式复制数据的能力。良好的拟合模型是与数据合理一致且不需要重新指定的模型,并且在估计协方差结构模型中的路径之前还需要使用其测量模型。使用潜在变量构建了四个结构的基线模型以及无,1、2、3或4个其他结构的组合,这些变量具有潜在变量:教育绩效,社会经济标签,自我概念和父母权威,每增加两个数字二或零构造。我们考虑了16个渐进式嵌套模型,这些模型从基线模型开始,使用来自建模样本的数学成人学习者数据并采用了一些常用的较大拟合指数(NFI,NNFI,CFI,GFI,PGFI等)Usluel等。 (2008)测试模型的适用性。提出了基于协方差结构模型分析结果的模型拟合度量。结构方程建模;伯努利数字;潜在构造;教育表现

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