Nonlinear Relations among Latent Variables

Jolynn Pek and Sonya K. Sterba and Bethany E. Kok and Daniel J. Bauer
University of North Carolina at Chapel Hill

This web page generates semiparametric estimates of the regression function for two latent variables. A mixture of linear structural equation models must first be fit to the data. The mixing probabilities (π) and latent variable model parameters (labeled in the diagram below) are then input into the boxes provided.

Empirical example on positive emotions and heuristic processing Mx output Mplus output

Empirical example on negative emotions and heuristic processing Mx output Mplus output

                          

 Label for η1:     Label for η2:
 Number of classes:
 Class 1: π = α1 = α2 = β21 = ψ11 = ψ22 =
Show class information

References

Pek, J., Sterba, S. K., Kok, B. E., & Bauer, D. J. (in preparation). Visualizing nonlinear relations among latent variables.

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