Department of Statistics, University of Washington, Seattle, WA, USA.
Department of Statistics, University of California, Davis, Davis, CA, USA.
Multivariate Behav Res. 2024 Sep-Oct;59(5):1077-1097. doi: 10.1080/00273171.2024.2372635. Epub 2024 Jul 12.
We implement an analytic approach for ordinal measures and we use it to investigate the structure and the changes over time of self-worth in a sample of adolescents students in high school. We represent the variations in self-worth and its various sub-domains using entropy-based measures that capture the observed uncertainty. We then study the evolution of the entropy across four time points throughout a semester of high school. Our analytic approach yields information about the configuration of the various dimensions of the self together with time-related changes and associations among these dimensions. We represent the results using a network that depicts self-worth changes over time. This approach also identifies groups of adolescent students who show different patterns of associations, thus emphasizing the need to consider heterogeneity in the data.
我们采用了一种分析方法来处理有序尺度，并将其应用于研究高中生样本中自我价值感的结构和随时间的变化。我们使用基于熵的测度来表示自我价值感及其各个子领域的变化，这些测度可以捕捉到观察到的不确定性。然后，我们研究了在整个高中学期的四个时间点上，熵的演变情况。我们的分析方法提供了有关自我各个维度的配置以及这些维度之间随时间的变化和关联的信息。我们使用一个网络图来表示随时间变化的自我价值感，展示结果。这种方法还可以识别出具有不同关联模式的青少年学生群体，从而强调需要考虑数据的异质性。
