Group-based modeling of development

By Dan Nagin. 2005

2,265 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Genetics

View Paper: https://www.semanticscholar.org/paper/7f25529349143ba19c90218531caf0bccf701516

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Citations in the corpus

Group-Based Trajectory Modeling: An Overview (2014, methodology): “2 of Nagin (2005) , for count data P.Yi/ is specified as the zero-inflated Poisson distribution, for censored data it is specified as the censored normal distribution, and for binary data, it is specified as the binary logit distribution.”
Trajectories of psychological need satisfaction from early to late adolescence as a predictor of adjustment in school (2014, methodology): “The present study will test whether there are distinct patterns of perceived need satisfaction from the end of elementary school to the end of high school using GBTM, therefore allowing us to estimate whether students’ trajectories of PNS in school differ across subgroups of students (i.e., are hete”
Overdispersion and Poisson Regression (2008, background): “More extensive discussions of heterogeneity can be found in the influential work Nagin and Land (1993) and in several subsequent papers and books (e.g., D’Unger et al. 1998; Nagin 2005 ).”
Trajectories of Prosocial Behavior and Physical Aggression in Middle Childhood: Links to Adolescent School Dropout and Physical Violence (2006, background): “All probabilities were higher than .80, a value that is generally assumed to imply a good model fit to the data ( Nagin, 2005 ).”
Trajectories of school engagement during adolescence: implications for grades, depression, delinquency, and substance use. (2011, background): “For instance, group-based mixture models lend themselves to identifying the various trajectories of school engagement that may be qualitatively different among subpopulations of adolescents (Nagin, 2005).”
Advances in Group-Based Trajectory Modeling and an SAS Procedure for Estimating Them (2007, methodology): “This multitrajectory model is a form of the so-called constrained dualtrajectory model described in Chapter 8 of Nagin (2005).”
Positive and Negative Developmental Trajectories in U.S. Adolescents: Where the Positive Youth Development Perspective Meets the Deficit Model (2008, methodology): “To analyze developmental trajectories, a finite mixture model approach was used (eg, Nagin, 2005 ) to estimate trajectories for each of the four longitudinal constructs of interest (ie, PYD, contribution, depressive symptoms, and risk/problem behaviors).”
Exploring the Effect of Exposure to Short-Term Solitary Confinement Among Violent Prison Inmates (2016, methodology): “The analysis was further extended to account for potential underlying between-group (i.e., latent) heterogeneity post-violence using finite-mixture-modeling (see Nagin 2005).”
Family and Religious Characteristics' Influence on Delinquency Trajectories from Adolescence to Young Adulthood (2009, methodology): “Because I use a unique set of parameters to estimate each trajectory, the shapes of the trajectories can vary by group (Nagin 2005).”