New developments in latent variable panel analyses of longitudinal data

Abstract

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.

Keywords

Structural equation modelingLatent variableLatent variable modelEconometricsPanel dataNull hypothesisPsychologyLatent growth modelingFactorialPanel analysisVariable (mathematics)Computer scienceCognitive psychologyMathematicsArtificial intelligenceMachine learningDevelopmental psychology

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Publication Info

Year: 2007
Type: article
Volume: 31
Issue: 4
Pages: 357-365
Citations: 629
Access: Closed

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APA Style

                            
                                
                                    Todd D. Little, 
                                
                                    Kristopher J. Preacher, 
                                
                                    James P. Selig
                                
                                et al.
                            
                            (2007). 
                            New developments in latent variable panel analyses of longitudinal data. 
                            International Journal of Behavioral Development
                            , 31
                            (4)
                            , 357-365.
                            https://doi.org/10.1177/0165025407077757
                        

Identifiers

DOI: 10.1177/0165025407077757