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Direct linkTong, Xin; Zhang, Zhiyong – Multivariate Behavioral Research, 2012
Growth curve models with different types of distributions of random effects and of intraindividual measurement errors for robust analysis are compared. After demonstrating the influence of distribution specification on parameter estimation, 3 methods for diagnosing the distributions for both random effects and intraindividual measurement errors…
Descriptors: Models, Robustness (Statistics), Statistical Analysis, Error of Measurement
Grimm, Kevin J.; Ram, Nilam; Estabrook, Ryne – Multivariate Behavioral Research, 2010
Growth mixture models (GMMs; B. O. Muthen & Muthen, 2000; B. O. Muthen & Shedden, 1999) are a combination of latent curve models (LCMs) and finite mixture models to examine the existence of latent classes that follow distinct developmental patterns. GMMs are often fit with linear, latent basis, multiphase, or polynomial change models…
Descriptors: Models, Computer Software, Programming, Statistical Analysis
Van Horn, M. Lee; Fagan, Abigail A.; Jaki, Thomas; Brown, Eric C.; Hawkins, J. David; Arthur, Michael W.; Abbott, Robert D.; Catalano, Richard F. – Multivariate Behavioral Research, 2008
There is evidence to suggest that the effects of behavioral interventions may be limited to specific types of individuals, but methods for evaluating such outcomes have not been fully developed. This study proposes the use of finite mixture models to evaluate whether interventions, and, specifically, group randomized trials, impact participants…
Descriptors: Intervention, Adolescents, Models, Behavior Problems
