General Growth Mixture Analysis with Antecedents and Consequences of Change

  • Hanno Petras
  • Katherine Masyn


Many studies of youth, adolescents, and adults related to delinquent, antisocial, and criminal offending, have utilized a language of trajectory typologies to describe individual differences in the behavioral course manifest in their longitudinal data. The two most common statistical methods currently in use are the semiparametric group-based modeling, also known as latent class growth analysis and general growth mixture analysis, with the latter method being the focus of this chapter. In concert with the growing popularity of these data-driven, group-based methods for studying developmental and life-course behavior trajectories have come active and spirited ontological discussions about the nature of the emergent trajectory groups resulting from the analyses. In this chapter, we presuppose that there are analytic, empirical, and substantive advantages inherent in using discrete components to (partially) describe population heterogeneity in longitudinal processes. Conceptually as well as empirically, we will discuss the use of auxiliary information in terms of antecedents and consequences of trajectory group membership. The inclusion of auxiliary information in growth mixture analysis is a necessary step in understanding as well as evaluating the fidelity and utility of the resultant trajectory profiles from a given study, regardless of one’s beliefs about the veracity of the method itself.


Latent Class Class Membership Distal Outcome Growth Mixture Model Latent Growth Curve Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We like to thank Alex Piquero, David Weisburd, Nicholas Ialongo and Bengt Muthén for their helpful comments on a prior draft of this manuscript.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Hanno Petras
    • 1
  • Katherine Masyn
    • 2
  1. 1.Department of Criminology and Criminal JusticeUniversity of MarylandCollege ParkUSA
  2. 2.Department of Human and Community DevelopmentUniversity of California DavisDavisUSA

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