Publications related to multilevel structural equation modeling

using xxM
  1. Branum-Martin, L. (2013). Multilevel modeling: Practical examples to illustrate a special case of SEM (pp. 95-124). In Y. Petscher, C. Schatschneider, & D.L. Compton (Eds.) Applied quantitative analysis in education and social sciences. New York: Routledge.
  2. Mehta, P. (2013). N-level structural equation modeling (pp. 329-362). In Y. Petscher, C. Schatschneider, & D.L. Compton (Eds.) Applied quantitative analysis in education and social sciences. New York: Routledge.
key multilevel structural equation modeling references
  1. Mehta, P. D., & Neale, M. C. (2005). People Are Variables Too: Multilevel Structural Equations Modeling. Psychological Methods. 5, 259-284.
  2. Mehta, P. D., & West, S. G. (2000). Putting the individual back into individual growth curves. Psychological Methods. 5, 23-43.
  3. Muthén, B. & Asparouhov, T. (2011). Beyond multilevel regression modeling: Multilevel analysis in a general latent variable framework. In J. Hox & J.K. Roberts (eds), Handbook of Advanced Multilevel Analysis, pp. 15-40. New York: Taylor and Francis.
  4. Rabe-Hesketh, S. and Skrondal, A. (2007). Multilevel and latent variable modeling with composite links and exploded likelihoods. Psychometrika, 72, 123-140.
  5. Lockwood, J., McCaffrey, D., Mariano, L., & Setodji, C. (2007). Bayesian methods for scalable multivariate value-added assessment. Journal of Educational and Behavioral Statistics, 32, 125–150.
  6. Bates, D., Maechler, M., Bolker, B., & Walker, S. (2013). Lme4: Linear mixed-effects model using Eigen and S4. R package version 1.0-5.
  7. Bates, D. (2010). Lme4: Mixed-effects modeling with R [On-line document]. URL
  8. Preacher, K. J., Zhang, Z., & Zyphur, M. J. (2011). Alternative methods for assessing mediation in multilevel data: The advantages of multilevel SEM. Structural Equation Modeling, 18, 161-182.
  9. Preacher, K. J., Zyphur, M. J., & Zhang, Z. (2010). A general multilevel SEM framework for assessing multilevel mediation. Psychological Methods15, 209-233.
  10. Curran, P. J. (2003). Have multilevel models been structural equation models all along? Multivariate Behavioral Research, 38, 529 –569.
  11. Bauer, D. J. (2003). Estimating multilevel linear models as structural models. Journal of Educational and Behavioral Statistics, 28, 135–167.
  12. du Toit, S., & du Toit, M. (2003). Multilevel structural equation modeling. In J. De Leeuw & I. G. G. Kreft (Eds.), Handbook of quantitative multilevel analysis (pp. 273–321). Boston:
  13. Bentler, P. M., & Liang, J. (2003). Two-level mean and covariance structures: Maximum likelihood via and EM algorithm. In S. P. Reise & N. Duan (Eds.), Multilevel modeling: Methodological advances, issues, and applications (pp. 53–70). Hillsdale, NJ: Erlbaum.
  14. Goldstein, H., & Browne, W. J. (2002). Multilevel factor analysis modelling using Markov Chain Monte Carlo (MCMC) estima- tion. In G. Marcoulides & I. Moustaki (Eds.), Latent variable and latent structure models (pp. 225–243). Hillsdale, NJ: Erlbaum.
  15. McDonald, R. P. (1993). A general model for two level data with responses missing at random. Psychometrika, 58, 575–585.
  16. Skrondal, A., & Rabe-Hesketh, S. (2004). Generalized latent variable modeling: Multilevel, longitudinal and structural equation models. Boca Raton, FL: Chapman & Hill.
  17. Willett, J. B., & Sayer, A. G. (1994). Using covariance structure analysis to detect correlates and predictors of individual change over time. Psychological Bulletin, 116, 363–381.