title: Group-based trajectory modeling in clinical research.
abstract: Group-based trajectory models are increasingly being applied in clinical research to map the developmental course of symptoms and assess heterogeneity in response to clinical interventions. In this review, we provide a nontechnical overview of group-based trajectory and growth mixture modeling alongside a sampling of how these models have been applied in clinical research. We discuss the challenges associated with the application of both types of group-based models and propose a set of preliminary guidelines for applied researchers to follow when reporting model results. Future directions in group-based modeling applications are discussed, including the use of trajectory models to facilitate causal inference when random assignment to treatment condition is not possible.
authors.affiliation: Heinz School of Public Policy, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213-3890, USA. dn03@andrew.cmu.edu
authors.forename: Daniel S
authors.initials: DS
authors.lastname: Nagin
authors.forename: Candice L
authors.initials: CL
authors.lastname: Odgers
mesh_terms: D035843:Biomedical Research / Q000379:methods* / Q000706:statistics & numerical data*; D006801:Humans; D008960:Models, Psychological; D011586:Psychology, Clinical / Q000379:methods* / Q000706:statistics & numerical data*