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Curve of Factors Model: A Latent Growth Modeling Approach for Educational Research

机译:要素曲线模型:教育研究的潜在增长建模方法

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摘要

A first-order latent growth model assesses change in an unobserved construct from a single score and is commonly used across different domains of educational research. However, examining change using a set of multiple response scores (e.g., scale items) affords researchers several methodological benefits not possible when using a single score. A curve of factors (CUFFS) model assesses change in a construct from multiple response scores but its use in the social sciences has been limited. In this article, we advocate the CUFFS for analyzing a construct’s latent trajectory over time, with an emphasis on applying this model to educational research. First, we present a review of longitudinal factorial invariance, a condition necessary for ensuring that the measured construct is the same across time points. Next, we introduce the CUFFS model, followed by an illustration of testing factorial invariance and specifying a univariate and a bivariate CUFFS model to longitudinal data. To facilitate implementation, we include syntax for specifying these statistical methods using the free statistical software R.
机译:一阶潜在增长模型通过单个分数评估未观察到的结构的变化,并且通常用于教育研究的不同领域。但是,使用一组多个响应评分(例如,量表项目)检查更改会为研究人员提供一些使用单个评分时无法实现的方法学优势。因子曲线(CUFFS)模型从多个响应得分评估结构的变化,但其在社会科学中的应用受到限制。在本文中,我们提倡CUFFS分析一段时间内构造物的潜在轨迹,重点是将该模型应用于教育研究。首先,我们介绍了纵向因式不变性,这是确保测得的结构在各个时间点相同的必要条件。接下来,我们介绍CUFFS模型,然后说明测试因式不变性并为纵向数据指定单变量和双变量CUFFS模型。为了便于实施,我们包括使用免费统计软件R指定这些统计方法的语法。

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