THE TRAIT-STATE-ERROR MODEL FOR MULTIWAVE DATA
THE TRAIT-STATE-ERROR MODEL FOR MULTIWAVE DATA
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DOI：
10.1037/0022-006x.63.1.52
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发表时间：
1995-02-01
影响因子：
5.9
通讯作者：
ZAUTRA, A
中科院分区：
文献类型：
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作者：
KENNY, DA;ZAUTRA, A
尽管临床心理学的研究人员经常收集许多人多次做出反应的数据，但没有一种标准的方法来分析这些数据。 描述了一种新的方法来分析这些数据。 有人提出，一个人目前对一个变量的立场是由3个方差来源引起的：一个不改变的术语（特质），一个改变的术语（状态）和一个随机术语（错误）。 它示出了如何结构方程模型可以用来估计这样的模型。 一个扩展的例子中，变量之间的相关性是完全不同的特质，状态和错误的水平。
Although researchers in clinical psychology routinely gather data in which many individuals respond at multiple times, there is not a standard way to analyze such data. A new approach for the analysis of such data is described. It is proposed that a person's current standing on a variable is caused by 3 sources of variance: a term that does not change (trait), a term that changes (state), and a random term (error). It is shown how structural equation modeling can be used to estimate such a model. An extended example is presented in which the correlations between variables are quite different at the trait, state, and error levels.