Growth Mixture Modeling is a longitudinal latent variable modeling approach that identifies unobserved subpopulations exhibiting distinct developmental trajectories within a heterogeneous population by simultaneously estimating multiple growth trajectory patterns and class membership probabilities.
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3.4K
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1.3K
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2017–2026
400
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858
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18
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13
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10
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10
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Columbia University
New York, United States
26 h-index
56 publications
4.9K citations
New York University
New York, United States
24 h-index
71 publications
4.2K citations
King's College London
London, United Kingdom
22 h-index
76 publications
6.6K citations
Johns Hopkins University
Baltimore, United States
20 h-index
60 publications
4.2K citations
University College London
London, United Kingdom
20 h-index
77 publications
5.5K citations
University of North Carolina at Chapel Hill
Chapel Hill, United States
18 h-index
37 publications
5.3K citations
University of Minnesota
Minneapolis, United States
17 h-index
33 publications
3.1K citations
University of Washington
Seattle, United States
17 h-index
30 publications
2.2K citations
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- Structural Equation Modeling A Multidisciplinary Journal
SEM · 27 publications · 17.2K citations
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- Development and Psychopathology
26 publications · 2.9K citations
19
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- Psychological Medicine
16 publications · 1.1K citations
15
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- PLoS ONE
16 publications · 582 citations
13
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- Journal of Consulting and Clinical Psychology
11 publications · 1K citations
11
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