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Recovery trajectories of IQ after pediatric TBI: A latent class growth modeling analysis

Journal of the International Neuropsychological Society, 2023
AbstractObjective: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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An Introduction to Latent Class Growth Analysis and Growth Mixture Modeling

Social and Personality Psychology Compass, 2007
Abstract 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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Integrating Person‐Centered and Variable‐Centered Analyses: Growth Mixture Modeling With Latent Trajectory Classes

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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Distributional Assumptions of Growth Mixture Models: Implications for Overextraction of Latent Trajectory Classes.

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
openaire   +2 more sources

Mixture Models: From Latent Classes/Profiles to Latent Growth, Transitions, and Multilevel Mixture Models

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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Application of Latent Class Growth Model to Longitudinal Analysis of Traffic Crashes

Transportation Research Record: Journal of the Transportation Research Board, 2011
One 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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Predictions of Individual Change Recovered With Latent Class or Random Coefficient Growth Models

Structural Equation Modeling: A Multidisciplinary Journal, 2014
Popular 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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Persistent High Non-High-Density Lipoprotein Cholesterol in Early Childhood: A Latent Class Growth Model Analysis

The Journal of Pediatrics, 2017
To examine patterns of non-high-density lipoprotein (HDL) cholesterol in early childhood and identify factors associated with persistent high non-HDL cholesterol in healthy urban children.We identified all children enrolled in a primary care practice-based research network called TARGet Kids!
Jordan M, Albaum   +8 more
openaire   +2 more sources

Growth Models for Categorical Response Variables: Standard, Latent-Class, and Hybrid Approaches

2017
Transitional models such as Markov-type models concentrate on changes between consecutive time points. Marginal models can be used to investigate changes in univariate distributions, and random-effects or growth models study development of individuals over time.
openaire   +2 more sources

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