主观幸福感的潜在轨迹:潜在增长曲线和潜在阶级增长模型的应用

Esra Sozer-Boz, Nilufer Kahraman
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引用次数: 0

摘要

本研究利用潜在成长曲线模型和潜在类别成长分析,提出一个三阶段的测量模型。该测量模型是通过一项为期四周的前瞻性研究收集的重复数据来说明的,该研究跟踪了志愿大学生的主观幸福感(n=154)。首先,估计了几个无条件增长模型,以定义能更好地代表个人增长轨迹的模型。其次,我们制定了几个条件增长模型来检验协变量的有效性,这些协变量被假设用来解释生长因子中观察到的方差。最后,估计潜在类别模型,进一步探索不同的潜在轨迹类别。结果表明,学生的主观幸福感随着时间的推移而变化,这种变化的速度,以及它的协变量,在整个样本中不是恒定的。这项研究清楚地说明了纵向测量方法如何在重复测量可用时增强发现的范围和推断的深度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Latent Trajectories of Subjective Well-Being: An Application of Latent Growth Curve and Latent Class Growth Modeling
This study proposed a three-stage measurement model utilizing the Latent Growth Curve Modeling and Latent Class Growth Analysis. The measurement model was illustrated using repeated data collected through a four-week prospective study tracking the subjective well-being of volunteer college students (n=154). Firstly, several unconditional growth models were estimated to define the model providing a better representation of individual growth trajectories. Secondly, several conditional growth models were formulated to test the usefulness of covariate variables hypothesized to explain observed variance in growth factors. Finally, latent class models were estimated to explore different latent trajectory classes further. Results showed that students' subjective well-being changed over time, and the rate of this change, as well as its covariates, were not constant for the entire sample. This study clearly illustrates how a longitudinal measurement approach can enhance the scope of findings and the depth of inferences when repeated measurements are available.
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