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Latent Growth Modeling of Longitudinal Data: A Finite Growth Mixture Modeling Approach
Structural Equation Modeling: A Multidisciplinary Journal, 2001Recent developments in finite mixture modeling allow for the identification of different developmental processes in distinct but unobserved subgroups within a population. The new approach, described within the general growth mixture modeling framework (Muthen, 2001, in press), extends conventional random coefficient growth models to incorporate a ...
Fuzhong Li +3 more
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An Introduction to Latent Class Growth Analysis and Growth Mixture Modeling
Social and Personality Psychology Compass, 2007Abstract In recent years, there has been a growing interest among researchers in the use of latent class and growth mixture modeling techniques for applications in the social and psychological sciences, in part due to advances in and availability of computer software designed for this purpose (e.g., Mplus and SAS Proc Traj).
Tony Jung, K. A. S. Wickrama
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Identifying trajectories of adolescent smoking: An application of latent growth mixture modeling.
Health Psychology, 2001The goal of the current study was to identify discrete longitudinal patterns of change in adolescent smoking using latent growth mixture modeling. Five distinct longitudinal patterns were identified. A group of early rapid escalators was characterized by early escalation (at age 13) that rapidly increased to heavy smoking.
Craig R. Colder +7 more
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2022
This seminar introduces mixture modeling and explores its application in applied psychology research and beyond. Topics and worked examples include latent class analysis (LCA), latent profile analysis (LPA), LCA/LPA with covariates, multilevel LCA/LPA, growth mixture modeling (GMM), and latent transition analysis (LTA).
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This seminar introduces mixture modeling and explores its application in applied psychology research and beyond. Topics and worked examples include latent class analysis (LCA), latent profile analysis (LPA), LCA/LPA with covariates, multilevel LCA/LPA, growth mixture modeling (GMM), and latent transition analysis (LTA).
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The Journal of Educational Research, 2012
ABSTRACT Addressing the academic needs of a growing student population with culturally and linguistically diverse characteristics is one of the challenges facing educators. This study used data from the Early Childhood Longitudinal Study to test for differences in patterns of mathematics growth (e.g., high, middle, and low performance groups) in Latino
Sehee Hong, Sukkyung You
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ABSTRACT Addressing the academic needs of a growing student population with culturally and linguistically diverse characteristics is one of the challenges facing educators. This study used data from the Early Childhood Longitudinal Study to test for differences in patterns of mathematics growth (e.g., high, middle, and low performance groups) in Latino
Sehee Hong, Sukkyung You
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Piecewise Linear–Linear Latent Growth Mixture Models With Unknown Knots
Educational and Psychological Measurement, 2013Latent growth curve models with piecewise functions are flexible and useful analytic models for investigating individual behaviors that exhibit distinct phases of development in observed variables. As an extension of this framework, this study considers a piecewise linear–linear latent growth mixture model (LGMM) for describing segmented change of ...
Nidhi Kohli +2 more
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Psychopathology and resilience following traumatic injury: A latent growth mixture model analysis.
Rehabilitation Psychology, 2010To investigate trajectories of PTSD and depression following traumatic injury using latent class growth curve modeling.A longitudinal study of 330 injured trauma survivors was conducted and participants were assessed during hospitalization, and at 1, 3, and 6 months follow-up.
Terri A, deRoon-Cassini +3 more
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Psychological Methods, 2003
Growth mixture models are often used to determine if subgroups exist within the population that follow qualitatively distinct developmental trajectories. However, statistical theory developed for finite normal mixture models suggests that latent trajectory classes can be estimated even in the absence of population heterogeneity if the distribution of ...
Daniel J, Bauer, Patrick J, Curran
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Growth mixture models are often used to determine if subgroups exist within the population that follow qualitatively distinct developmental trajectories. However, statistical theory developed for finite normal mixture models suggests that latent trajectory classes can be estimated even in the absence of population heterogeneity if the distribution of ...
Daniel J, Bauer, Patrick J, Curran
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Journal of Youth and Adolescence, 2004
Using data from a community sample of 1218 boys and girls (mean age at the first wave was 15.5 years), this longitudinal study examined several covariates—adjustment problems, poor academic achievement, negative life events, and unsupportive family environments—of distinctive trajectories of juvenile delinquency. Latent growth mixture modeling analysis
Margit Wiesner, Michael Windle
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Using data from a community sample of 1218 boys and girls (mean age at the first wave was 15.5 years), this longitudinal study examined several covariates—adjustment problems, poor academic achievement, negative life events, and unsupportive family environments—of distinctive trajectories of juvenile delinquency. Latent growth mixture modeling analysis
Margit Wiesner, Michael Windle
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The International Journal of Aviation Psychology, 2015
Latent growth mixture modeling is a statistical approach that models longitudinal data, grouping individuals who share similar longitudinal data patterns into latent classes. We evaluated the application of this method in a sample of ab initio pilot applicants (N = 297), using longitudinal data collected from a military flight-screening program (where ...
Gomes, A., Dias, J. G.
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Latent growth mixture modeling is a statistical approach that models longitudinal data, grouping individuals who share similar longitudinal data patterns into latent classes. We evaluated the application of this method in a sample of ab initio pilot applicants (N = 297), using longitudinal data collected from a military flight-screening program (where ...
Gomes, A., Dias, J. G.
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