Effects of Missing Data Methods in Structural Equation Modeling With Nonnormal Longitudinal Data

2009 ◽  
Vol 16 (1) ◽  
pp. 70-98 ◽  
Author(s):  
Tacksoo Shin ◽  
Mark L. Davison ◽  
Jeffrey D. Long
Keyword(s):  
Structural Equation Modeling ◽  
Missing Data ◽  
Longitudinal Data ◽  
Structural Equation ◽  
Equation Modeling

New developments in latent variable panel analyses of longitudinal data

2007 ◽  
Vol 31 (4) ◽  
pp. 357-365 ◽  
Author(s):  
Todd D. Little ◽  
Kristopher J. Preacher ◽  
James P. Selig ◽  
Noel A. Card
Keyword(s):  
Structural Equation Modeling ◽  
Longitudinal Data ◽  
Latent Variables ◽  
Latent Variable ◽  
Structural Equation ◽  
Null Model ◽  
Factorial Invariance ◽  
Equation Modeling ◽  
New Developments ◽  
Mediated Effects

We review fundamental issues in one traditional structural equation modeling (SEM) approach to analyzing longitudinal data — cross-lagged panel designs. We then discuss a number of new developments in SEM that are applicable to analyzing panel designs. These issues include setting appropriate scales for latent variables, specifying an appropriate null model, evaluating factorial invariance in an appropriate manner, and examining both direct and indirect (mediated), effects in ways better suited for panel designs. We supplement each topic with discussion intended to enhance conceptual and statistical understanding.

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