Results 241 to 250 of about 451,168 (290)
Some of the next articles are maybe not open access.
Facilitating Growth Mixture Model Convergence in Preventive Interventions
Prevention Science, 2021Growth mixture models (GMMs) are applied to intervention studies with repeated measures to explore heterogeneity in the intervention effect. However, traditional GMMs are known to be difficult to estimate, especially at sample sizes common in single-center interventions.
Daniel McNeish +5 more
openaire +2 more sources
Unrestricted Mixture Models for Class Identification in Growth Mixture Modeling
Educational and Psychological Measurement, 2014Growth 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, especially when the assumption of proper model specification is violated.
Min Liu, Gregory R. Hancock
openaire +1 more source
Multilevel Growth Mixture Models for Classifying Groups
Journal of Educational and Behavioral Statistics, 2010This article introduces a multilevel growth mixture model (MGMM) for classifying both the individuals and the groups they are nested in. Nine variations of the general model are described that differ in terms of categorical and continuous latent variable specification within and between groups.
Palardy, G., Vermunt, J.K.
openaire +2 more sources
Handling Missing Data in Growth Mixture Models
Journal of Educational and Behavioral Statistics, 2023A Monte Carlo simulation was performed to compare methods for handling missing data in growth mixture models. The methods considered in the current study were (a) a fully Bayesian approach using a Gibbs sampler, (b) full information maximum likelihood using the expectation–maximization algorithm, (c) multiple imputation, (d) a two-stage multiple ...
Daniel Y. Lee, Jeffrey R. Harring
openaire +1 more source
Growth mixture models in longitudinal research
AStA Advances in Statistical Analysis, 2011Latent growth curve models as structural equation models are extensively discussed in various research fields (Curran and Muthen in Am. J. Community Psychol. 27:567–595, 1999; Duncan et al. in An introduction to latent variable growth curve modeling.
Reinecke, Jost, Seddig, Daniel
openaire +2 more sources
Latent Growth Modeling of Longitudinal Data: A Finite Growth Mixture Modeling Approach
Structural Equation Modeling: A Multidisciplinary Journal, 2001Recent developments in finite mixture modeling allow for the identification of different developmental processes in distinct but unobserved subgroups within a population. The new approach, described within the general growth mixture modeling framework (Muthen, 2001, in press), extends conventional random coefficient growth models to incorporate a ...
Fuzhong Li +3 more
openaire +1 more source
Mixture models for clustering multilevel growth trajectories
Computational Statistics & Data Analysis, 2014zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Ng, SK, McLachlan, GJ
openaire +3 more sources
Dynamic segmentation with growth mixture models
Advances in Data Analysis and Classification, 2016zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire +2 more sources
The potential of growth mixture modelling
Infant and Child Development, 2006NOT GMM VERSUS LCGA, BUT BOTH IN A GENERAL LATENT VARIABLE FRAMEWORK The authors bring up the important issue of choice of model within the general framework of mixture modelling, especially the choice between latent class growth analysis (LCGA) techniques developed by Nagin and colleagues versus GMM developed by Muthen and colleagues.
openaire +1 more source