Analyzing Latent State-Trait and Multiple-Indicator Latent Growth Curve Models as Multilevel Structural Equation Models

Analyzing Latent State-Trait and Multiple-Indicator Latent Growth Curve Models as Multilevel Structural Equation Models

Latent state-trait (LST) and latent growth curve (LGC) models are frequently used in the analysis of longitudinal data. Although it is well-known that standard single-indicator LGC models can be analyzed within either the structural equation modeling (SEM) or multilevel (ML; hierarchical linear mode...

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Bibliographic Details
Main Authors: Christian eGeiser, Jacob eBishop, Ginger eLockhart, Saul eShiffman, Jerry L. Grenard
Format: Article
Language:English
Published: Frontiers Media S.A. 2013-12-01
Series:Frontiers in Psychology
Subjects:
mood states
Latent state-trait analysis
multiple-indicator latent growth curve models
multilevel structural equation models
individually-varying and unequally-spaced time points
mixed-effects models
Online Access:http://journal.frontiersin.org/Journal/10.3389/fpsyg.2013.00975/full

Internet

http://journal.frontiersin.org/Journal/10.3389/fpsyg.2013.00975/full

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