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Predictions of Individual Change Recovered With Latent Class or Random Coefficient Growth Models
Structural Equation Modeling, 2014Popular longitudinal models allow for prediction of growth trajectories in alternative ways. In latent class growth models (LCGMs), person-level covariates predict membership in discrete latent classes that each holistically define an entire trajectory of change (e.g., a high-stable class vs. late-onset class vs. moderate-desisting class).
Sonya K Sterba, Daniel J Bauer
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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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Recovery trajectories of IQ after pediatric TBI: A latent class growth modeling analysis
Journal of the International Neuropsychological Society, 2023AbstractObjective:To identify latent trajectories of IQ over time after pediatric traumatic brain injury (TBI) and examine the predictive value of risk factors within and across recovery trajectories.Method:206 children ages 3–7 years at injury were included: 87 TBI (23 severe, 21 moderate, 43 complicated mild) and 119 orthopedic injury (OI).
Megan E. Narad +6 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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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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Application of Latent Class Growth Model to Longitudinal Analysis of Traffic Crashes
Transportation Research Record: Journal of the Transportation Research Board, 2011One of the most important and meaningful tasks in traffic safety is to describe how traffic crash risk changes over time. Over the past 20 years, much work has been done about this task. The recent introduction of latent class models to analyze crash data has created a need to examine how these models could be used for longitudinal data analysis ...
Yichuan Peng, Dominique Lord
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Structural Equation Modeling: A Multidisciplinary Journal, 2007
Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, one unresolved issue in the application of mixture models is that there is not one commonly accepted statistical indicator for deciding on the number of classes in a study population ...
Karen L. Nylund +2 more
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Mixture modeling is a widely applied data analysis technique used to identify unobserved heterogeneity in a population. Despite mixture models' usefulness in practice, one unresolved issue in the application of mixture models is that there is not one commonly accepted statistical indicator for deciding on the number of classes in a study population ...
Karen L. Nylund +2 more
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Alcoholism: Clinical and Experimental Research, 2000
Background: Many alcohol research questions require methods that take a person‐centered approach because the interest is in finding heterogeneous groups of individuals, such as those who are susceptible to alcohol dependence and those who are not. A person‐centered focus also is useful with longitudinal data to represent heterogeneity in developmental
B, Muthén, L K, Muthén
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Background: Many alcohol research questions require methods that take a person‐centered approach because the interest is in finding heterogeneous groups of individuals, such as those who are susceptible to alcohol dependence and those who are not. A person‐centered focus also is useful with longitudinal data to represent heterogeneity in developmental
B, Muthén, L K, Muthén
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Health Services and Outcomes Research Methodology, 2012
Two common approaches for studying trajectories of change are standard growth curve modeling (GCM) and latent class growth modeling (LCM) (Singer and Willett, Applied longitudinal data analysis. Modeling change and event occurrence. Oxford University Press, New York, 2003; Nagin, Group-based modeling of development. Harvard University Press, Cambridge,
Mark A. Ferro, Kathy N. Speechley
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Two common approaches for studying trajectories of change are standard growth curve modeling (GCM) and latent class growth modeling (LCM) (Singer and Willett, Applied longitudinal data analysis. Modeling change and event occurrence. Oxford University Press, New York, 2003; Nagin, Group-based modeling of development. Harvard University Press, Cambridge,
Mark A. Ferro, Kathy N. Speechley
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2011
Growth mixture modeling has gained much attention in applied and methodological social science research recently, but the selection of the number of latent classes for such models remains a challenging issue. This problem becomes more serious when one of the key assumptions of this model, proper model-specification is violated.
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Growth mixture modeling has gained much attention in applied and methodological social science research recently, but the selection of the number of latent classes for such models remains a challenging issue. This problem becomes more serious when one of the key assumptions of this model, proper model-specification is violated.
openaire +1 more source