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首页> 外文期刊>Structural equation modeling >Modeling Self-Regulation as a Process Usinga Multiple Time-Scale Multiphase Latent Basis Growth Model
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Modeling Self-Regulation as a Process Usinga Multiple Time-Scale Multiphase Latent Basis Growth Model

机译:使用多时标多相潜在基增长模型将自我调节建模为一个过程

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摘要

Measurement burst designs, wherein individuals are measured intensively during multiple periods (i.e., bursts), have created new opportunities for studying change at multiple time scales. This article develops a model that might be useful in situations where the functional form of short-term change is unknown, might consist of multiple phases, and might change over the long term. Specifically, we combine measurement of intraindividual entropy, a latent basis growth model, a multiphase growth model, and a growth model with covariates into a unified framework that could help accommodate the complexity of patterns that emerge in multiple time-scale categorical data streams. Empirical data from a longitudinal study of young children's behavior during laboratory tasks designed to induce frustration are used to illustrate the utility of the proposed model for simultaneously describing intratask (short-term) change in self-regulation and developmental (long-term) shifts in intratask change.
机译:其中在多个时间段(即突发)中对个体进行密集测量的测量突发设计为研究多个时间尺度的变化创造了新的机会。本文开发了一个模型,该模型在短期更改的功能形式未知,可能包含多个阶段以及可能长期更改的情况下可能很有用。具体来说,我们将个体内熵的度量,潜在增长模型,多阶段增长模型以及带有协变量的增长模型组合到一个统一的框架中,该框架可以帮助适应出现在多个时标分类数据流中的模式的复杂性。一项旨在对挫折感进行设计的实验室任务中的幼儿行为的纵向研究的经验数据用于说明所提出的模型在同时描述任务中(短期)自我调节和发育(长期)变化方面的效用。任务内更改。

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