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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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Latent growth mixture models: an important new tool for developmental researchers
Infant and Child Development, 2006AbstractThis manuscript by Connell and Frye (Infant Child Dev 2006; 15(6): 609–621) provides a clear example of the application of latent growth mixture models (LGMM) to the development of antisocial behaviour in adolescence. The LGMM approach is discussed in the context of this example, and factors influencing the results achieved with these methods ...
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Journal of Occupational and Organizational Psychology, 2010
The aim of the present three‐wave follow‐up study ( n = 335) among employees of an employment agency was to investigate the association between job resources and work‐related flow utilizing both variable‐ and person‐oriented approaches.
Mäkikangas, A. +3 more
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The aim of the present three‐wave follow‐up study ( n = 335) among employees of an employment agency was to investigate the association between job resources and work‐related flow utilizing both variable‐ and person‐oriented approaches.
Mäkikangas, A. +3 more
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Latent Markov and growth mixture models: a comparison
2015We compare two alternative approaches of modeling longitudinal data in order to find patterns of change according to the available covariates, accounting for the unobserved heterogeneity in the population of interest. We refer to the Latent Markov (LM) model and to the Growth Mixture Model (GMM). We illustrate the main results by using real data on the
PENNONI, FULVIA, ROMEO, ISABELLA
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Psychological Methods
McNeish et al. argue for the general use of covariance pattern growth mixture models because these models do not involve the assumption of random effects, demonstrate high rates of convergence, and are most likely to identify the correct number of latent subgroups.
Phillip K. Wood +2 more
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McNeish et al. argue for the general use of covariance pattern growth mixture models because these models do not involve the assumption of random effects, demonstrate high rates of convergence, and are most likely to identify the correct number of latent subgroups.
Phillip K. Wood +2 more
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Mixture Mixed Models: Biennial Growth as a Latent Variable in Coffee Bean Progenies
Crop Science, 2019ABSTRACTStatistical analysis of Coffea arabica L. progeny production has been a great challenge. In this species, genotypes may present differential biennial behaviors due to different physiological responses to the environmental conditions, indicating a mixture of two subpopulations in the tested progenies.
Vieira Júnior, Indalécio Cunha +5 more
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Multilevel Latent Growth and Mixture Models
2020Ronald H. Heck, Scott L. Thomas
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Residual-Based Algorithm for Detecting Mixtures in Latent Growth Models
Proceedings of the 2020 AERA Annual Meeting, 2020openaire +1 more source