Recent Papers

• Asparouhov, T., Muthén, B. & Morin, A. J. S. (2015). Bayesian structural equation modeling with cross-loadings and residual covariances: Comments on Stromeyer et al.

• Muthén, B. & Asparouhov T. (2015). Growth mixture modeling with non-normal distributions. Statistics in Medicine, 34:6, 1041–1058. doi: 10.1002/sim6388

• Asparouhov, T. & Muthén, B. (2014). General random effect latent variable modeling: Random subjects, items, contexts, and parameters. Version 2. Forthcoming in the edited book "Advances in Multilevel Modeling for Educational Research: Addressing Practical Issues Found in Real-World Applications”.

• Asparouhov, T. & Muthén, B. (2014). Auxiliary variables in mixture modeling: Using the BCH method in Mplus to estimate a distal outcome model and an arbitrary second model. Web note 21.

• Asparouhov, T. & Muthén B. (2014). Structural equation models and mixture models with continuous non-normal skewed distributions. Web note 19. Version 2. Download Mplus inputs and outputs used in this paper here.

• Muthén, B. & Asparouhov, T. (2014). IRT studies of many groups: The alignment method. Frontiers in Psychology, Volume 5, DOI: 10.3389/fpsyg.2014.00978

• Asparouhov, T. & Muthen, B. (2014). Residual associations in latent class and latent transition analysis. Structural Equation Modeling: A Multidisciplinary Journal. DOI:10.1080/10705511.2014.935844

• Muthén, B. & Asparouhov, T. (2014). Causal effects in mediation modeling: An introduction with applications to latent variables. Structural Equation Modeling: A Multidisciplinary Journal, 22(1), 12-23. DOI:10.1080/10705511.2014.935843

• Asparouhov, T. & Muthén, B. (2014). Auxiliary variables in mixture modeling: Three-step approaches using Mplus. Structural Equation Modeling: A Multidisciplinary Journal, 21:3, 329-341. The posted version corrects several typos in the published version. An earlier version of this paper was posted as web note 15. Appendices with Mplus scripts are available here.

• Asparouhov, T. & Muthén, B. (2014). Multiple-group factor analysis alignment. Structural Equation Modeling: A Multidisciplinary Journal, 21:4, 495-508. DOI: 10.1080/10705511.2014.919210. An earlier version of this paper was posted as web note 18. Mplus input, output, and data files for Web Note 18 Monte Carlo simulations are available here.

• Asparouhov, T. & Muthén, B. (2014). Using Mplus individual residual plots for diagnostic and model evaluation in SEM. Web note 20.

• Muthén, B. & Asparouhov, T. (2013). New methods for the study of measurement invariance with many groups. Mplus scripts are available here.

• Muthén, B. & Asparouhov, T. (2013). Item response modeling in Mplus: A multi-dimensional, multi-level, and multi-timepoint example.

• Version 7 papers are available here.