Supporting materials

The purpose of GMM and LCGA
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GMM and LCGA applied to categorical variables
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GMM and LCGA with covariates and distal outcomes, and further applications
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Recommended reading

  • Muthén, B. O., & Muthén, L. K. (2000). Integrating person-centered and variable-centered analyses: Growth mixture modeling with latent trajectory classes. Alcoholism: Clinical and Experimental Research, 24(6), 882–891.
  • Muthén, B.O. (2004). Latent variable analysis: growth mixture modeling and related techniques for longitudinal data. In Handbook of Quantitative Methodology for the Social Sciences, ed. D. Kaplan, pp. 345–68. Newbury Park, CA: Sage
  • Nagin, D.S. (2005). Group-Based Modeling of Development. Cambridge, MA: Harvard Univ. Press.
  • Nagin, D. S., Jones, B. L., Passos, V. L., & Tremblay, R. E. (2018). Group-based multi-trajectory modeling. Statistical Methods in Medical Research, 27(7), 2015–2023.
  • Feldman, B. J., Masyn, K. E., & Conger, R. D. (2009). New Approaches to Studying Problem Behaviors: A Comparison of Methods for Modeling Longitudinal, Categorical Adolescent Drinking Data. Developmental Psychology, 45(3), 652–676.
  • Haviland, A., Rosenbaum, P. R., Nagin, D. S., & Tremblay, R. E. (2008). Combining group-based trajectory modeling and propensity score matching for causal inferences in nonexperimental longitudinal data. Developmental Psychology, 44(2), 422–436.
  • Nagin, D., Pagani, L., Tremblay, R., & Vitaro, F. (2003). Life course turning points: The effect of grade retention on physical aggression. Development and Psychopathology, 15(2), 343-361.
  • Nagin, D. S., & Tremblay, R. E. (2001). Analyzing developmental trajectories of distinct but related behaviors: A group-based method. Psychological Methods, 6(1), 18–34.
  • Feng, Z., van den Broek, T., Perra, O., Cramm, J. M., & Nieboer, A. P. (2022). Longitudinal health behaviour patterns among adults aged ≥50 years in China and their associations with trajectories of depressive symptoms. Aging & Mental Health.