Sunbelt XXXI International Network for Social Network ... - INSNA

Actor Heterogeneity In Dynamic Influence And Selection ModelsKoskinen, Johan H.; Snijders, Tom A.Mathematical and Statistical Network ModelsStatistical Methods, Longitudinal Analysis, Stochastic Actor‐ Oriented ModelsSAT.PM2In the context of stochastic actor‐oriented models, actor heterogeneity poses the two inferential questions of what actors are different and with respect towhat effects they differ. Conditional on a specific choice of model and a subset of effects for which the homogeneity may be relaxed, a Bayesian latent classinference scheme takes actor heterogeneity into consideration. To guide us in the choice of model specification we propose to use diagnostics for detection ofheterogeneity. These aim to ascertain the presence of heterogeneity for actors and if some actors are extreme; and, what aspects of the evolution the actorsare heterogeneous with respect to. For a base‐line model score‐based methods and case‐deletion approaches are available to us. A selection of fitted modelsmay then be tested against each other and goodness of fit measures used to assess latent class homogeneity and separation.Affiliation Networks And Adolescent Problem BehaviorSoller, Brian; Browning, Christopher R.Adolescent Friendship NetworksTwo‐mode Data, Adolescents, Criminal Behavior, Drug Use, Affiliation NetworksFRI.AM2Research suggests dense social networks within collectivities protect against antisocial behavior among youth in part by increasing aggregate levels of socialcontrol. Studies also emphasize the importance of connections to social institutions in fostering access to resources and adolescent socialization. While theoryand research suggest that aggregate social cohesion and institutional affiliations may protect against problem behavior and adverse outcomes, mostconventional sampling techniques and questionnaires preclude the construction of objective measures of collective (e.g., school or neighborhood) networkproperties. Using data from Add Health, we compare the effects of aggregate measures of affiliation‐based network density (students connected to schoolactivities) and friendship network density on a host of individual outcomes across 113 schools in the US. Multilevel models of substance use, violentvictimization, delinquency, sexual activity, depression, and school attachment reveal significant effects of both aggregate density measures after controlling forindividual covariates, ego network density, and wave 1 controls. In addition, affiliation network density was more strongly associated with a number ofoutcomes than friendship network density. We discuss the utility of this new measure for research on problem behavior and its potential for capturingneighborhood‐based affiliation network density with clustered random samples.