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首页> 外文期刊>Procedia Computer Science >Latent Transition Analysis (LTA) : A Method for Identifying Differences in Longitudinal Change Among Unobserved Groups
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Latent Transition Analysis (LTA) : A Method for Identifying Differences in Longitudinal Change Among Unobserved Groups

机译:潜在转换分析(LTA):一种识别未观察组纵向变化差异的方法

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摘要

The latent transition analysis (LTA) model is a version of Latent Class Analysis (LCA) which is used in longitudinal data analysis. The goal of LTA is to examine the variation over time and to identify the association of repeated measures. LTA gives an elegant solution to study heterogeneous changes in longitudinal data. As a classic LCA, it assumes that the data consists of several unknown groups that have homogeneous choices. This paper aims to present a review of assess the performance of LTA to identify the differences in longitudinal differences among unobserved classes. An example of LTA application in educational assessment was developed to illustrate the process and to explore the change among the time in reading comprehension.
机译:潜在转换分析(LTA)模型是在纵向数据分析中使用的潜在类分析(LCA)的版本。 LTA的目标是检查随时间的变化,并确定重复措施的关联。 LTA提供了优雅的解决方案,用于研究纵向数据的异构变化。作为经典LCA,它假设数据包括几个具有均匀选择的未知组。本文旨在审查评估LTA的表现,以确定未观察的课程中纵向差异的差异。制定了教育评估中LTA应用的一个例子,以说明该过程,并探讨阅读理解的时间的变化。

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