Beyond autoregressive models: some implications of the trait-state distinction for the structural modeling of developmental change.
Beyond autoregressive models: some implications of the trait-state distinction for the structural modeling of developmental change.
复制标题
DOI：
10.2307/1130294
复制
发表时间：
1987-02
影响因子：
4.6
通讯作者：
Christopher Hertzog;J. Nesselroade
中科院分区：
文献类型：
--
作者：
Christopher Hertzog;J. Nesselroade
使用结构建模技术，以适应变化的概念，包括发展的，重复测量数据已经相当坚定，但不加批判地坚持自回归模型规格。自回归规范对重复测量的不加批判的应用没有考虑稳定性和变化概念的微妙之处（例如，特质与状态的区别），这些现已在行为研究文献中得到认可。我们回顾了特质和状态之间的基本区别，并研究了建模发展现象的不同可能性的影响。实证的例子说明的论点。
The use of structural modeling techniques to fit change concepts, including developmental ones, to repeated-measurements data has been rather firmly but uncritically wedded to autoregressive model specifications. The uncritical application of an autoregressive specification to repeated measures does not take into account subtleties of conceptions of stability and change (e.g., the trait-state distinction) that are now recognized in the behavioral research literature. We review the basic distinction between trait and state and examine the implications of the different possibilities for modeling developmental phenomena. The arguments are illustrated with empirical examples.