Longitudinal CFA vs Latent State-Trait Models

QuantFish insrructor Dr. Christian Geiser explains the relationship between conventional longitudinal confirmatory factor analysis models and latent state-trait (LST) models. He shows how you can obtain consistency and occasion-specificity coefficients from the LST model to determine whether constructs are trait-like or state-like.

#Mplus #Mplusforbeginners #statistics #CFA #SEM #LST #geiser #quantfish #statisticstutorials

LONGITUDINAL STRUCTURAL EQUATION MODELING COURSE:

LATENT STATE-TRAIT MODELING WITH MPLUS COURSE:

Dr. Geiser's BOOKS:

OTHER ON-DEMAND MPLUS COURSES:

GET IN TOUCH with DR. GEISER:

ABOUT THIS INSTRUCTOR:
Dr. Christian Geiser is a quantitative psychologist, author of two books on Mplus, and a leader in the development of latent variable techniques for complex data. With his accessible books and sought-after workshops, he has helped thousands of researchers and students around the world to achieve their analytic goals.

ABOUT QUANTFISH:

Some affiliate links may be included at no additional cost to purchasers.

[Sokratis_]

Hi Christian, first of all thank you for this extremely helpful video on the relationship between LCFA and LST models! My question is, isn't the assumption that both tau1 and tau2 have the same loadings on the trait factor too restrictive? For example, isn't it possible that in a given time point a factor has more trait variance and less situation-specific variance than in another time point where there could for example be more strong situational effects? I understand the explanation about identifiability but since in these models we would typically assume measurement invariance wouldn't we have enough degrees of freedom to freely estimate one of the loadings? Please, correct me if I am missing something.
Best wishes,
Socrates