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Persons as Contexts: Evaluating Between-Person and Within-Person Effects in Longitudinal Analysis

机译:作为背景的人:在纵向分析中评估人与人之间的影响

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摘要

Relationships among multiple variables over time are of interest in many developmental areas and are frequently examined using time-varying predictors in multilevel models. Yet an incomplete specification of time-varying predictors will usually result in biased model effects. Specifically, the impact of constant, between-person sources of variation must be differentiated from the impact of time-specific, within-person sources of variation -that is, persons should be modeled as contexts. The current didactic article expands upon previous work to address why and how to model persons as contexts in longitudinal analysis. An electronic appendix of syntax for estimating these models is also provided.
机译:随着时间的推移,多个变量之间的关系在许多开发领域中受到关注,并且经常在多级模型中使用时变预测变量进行检查。然而,时变预测变量的不完整规范通常会导致模型效果出现偏差。具体而言,必须将恒定的人际变异源的影响与特定于时间的人际变异源的影响区分开来,也就是说,应该将人建模为上下文。当前的教学文章扩展了先前的工作,以解决为什么以及如何在纵向分析中将人建模为情境。还提供了用于估计这些模型的语法的电子附录。

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