ERIC Number: EJ720519
Record Type: Journal
Publication Date: 2005-Sep
Reference Count: 32
Causal Inferences with Group Based Trajectory Models
Haviland, Amelia M.; Nagin, Daniel S.
Psychometrika, v70 n3 p557-578 Sep 2005
A central theme of research on human development and psychopathology is whether a therapeutic intervention or a turning-point event, such as a family break-up, alters the trajectory of the behavior under study. This paper lays out and applies a method for using observational longitudinal data to make more confident causal inferences about the impact of such events on developmental trajectories. The method draws upon two distinct lines of research: work on the use of finite mixture modeling to analyze developmental trajectories and work on propensity scores. The essence of the method is to use the posterior probabilities of trajectory group membership from a finite mixture modeling framework, to create balance on lagged outcomes and other covariates established prior to "t" for the purpose of inferring the impact of first-time treatment at "t" on the outcome of interest. The approach is demonstrated with an analysis of the impact of gang membership on violent delinquency based on data from a large longitudinal study conducted in Montreal.
Descriptors: Attribution Theory, Causal Models, Inferences, Longitudinal Studies, Psychological Studies, Violence, Delinquency, Foreign Countries, Group Membership, Males, Low Income Groups, Child Development, Developmental Psychology
Springer, 233 Spring Street, New York, NY 10013. Tel: 212-460-1539; Fax: 212-460-1594.
Publication Type: Journal Articles; Reports - Descriptive
Education Level: N/A
Authoring Institution: N/A
Identifiers - Location: Canada (Montreal)