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Call for papers: Conference on computational social science, April 2017, U-M

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Mon, Feb 13, 2017, noon:
Daniel Almirall, "Getting SMART about adaptive interventions"

Estimating Co-Occurring Behavioral Trajectories Within a Neighborhood Context: A Case Study of Multivariate Transition Models for Clustered Data

Archived Abstract of Former PSC Researcher

Cerda, M., B.N. Sanchez, Sandro Galea, M. Tracy, and S.L. Buka. 2008. "Estimating Co-Occurring Behavioral Trajectories Within a Neighborhood Context: A Case Study of Multivariate Transition Models for Clustered Data." American Journal of Epidemiology, 168(10): 1190-1203.

Comorbidity is well-documented in psychiatric and risk behavior epidemiology. The authors present a novel application of clustered multivariate transition models to study comorbidity within a clustered context. The authors used data from the Project on Human Development in Chicago Neighborhoods (1995-2002) to assess trajectories in substance use, problems with police, and antisocial behavior among 1,517 participants in 80 neighborhoods followed from ages 12-15 years through ages 18-21 years. The authors used pairwise odds ratios to quantify behavior comorbidity at the individual and neighborhood levels. Risk behaviors co-occurred within individuals at specific points in time: antisocial behavior and substance use were 3.37 times more likely to co-occur within an individual at wave 1, as compared with the co-occurrence of any 2 behaviors from different individuals, while substance use and police problems were 2.94 times more likely to co-occur than substance use and antisocial behavior at wave 2. The authors also evaluated sequential comorbidity. Antisocial behavior was sequentially comorbid with substance use and police problems: 31% of youths who had reported antisocial behavior at baseline reported police problems or drug use at wave 2. These models can prove instrumental in answering the persistent questions about possible sequential relations among problem behaviors.

DOI:10.1093/aje/kwn241 (Full Text)

PMCID: PMC2732958. (Pub Med Central)

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