An Overview of the Autoregressive Latent Trajectory (ALT) Model
An Overview of the Autoregressive Latent Trajectory (ALT) Model
复制标题
DOI：
10.1007/978-3-642-11760-2_5
复制
发表时间：
2010-01-01
期刊：
影响因子：
--
通讯作者：
Zimmer, Catherine
中科院分区：
文献类型：
--
作者：
Bollen, Kenneth A.;Zimmer, Catherine
自回归交叉滞后模型和潜增长曲线模型经常应用于纵向数据或面板数据。尽管它们经常被作为不同的、有时甚至是相互竞争的方法来介绍，但自回归潜轨迹（ALT）模型（博伦和柯伦，2004）将每种模型的主要特征组合成一个单一模型。本章：（1）介绍ALT模型；（2）描述该模型适用的情况；（3）提供ALT模型的一个实证示例；（4）向读者展示在该实证示例上运行ALT模型的输入和输出。最后讨论了ALT模型的局限性和扩展。我们的重点是连续变量的重复测量。
Autoregressive cross-lagged models and latent growth curve models are frequently applied to longitudinal or panel data. Though often presented as distinct and sometimes competing methods, the Autoregressive Latent Trajectory (ALT) model (Bollen and Curran, 2004) combines the primary features of each into a single model. This chapter: (1) presents the ALT model, (2) describes the situations when this model is appropriate, (3) provides an empirical example of the ALT model, and (4) gives the reader the input and output from an ALT model run on the empirical example. It concludes with a discussion of the limitations and extensions of the ALT model. Our focus is on repeated measures of continuous variables.