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Modeling Self-Regulation as a Process Using a Multiple Time-Scale Multiphase Latent Basis Growth Model

机译:使用多时标多相潜伏基础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 paper develops a model that may be useful in situations where the functional form of short-term change is unknown, may consist of multiple phases, and may 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 may 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:衡量突发事件的设计(在多个时期(即“突发”)中对个人进行密集的测量)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,该模型可能在短期变化的功能形式未知,可能由多个阶段组成并且可能长期变化的情况下很有用。具体来说,我们将个体内熵的度量,潜在增长模型,多阶段增长模型和带有协变量的增长模型组合到一个统一的框架中,这可以帮助适应出现在多个时间尺度分类数据流中的模式的复杂性。一项旨在对挫折感进行实验室任务的纵向研究对幼儿行为的纵向研究得出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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