Results 211 to 220 of about 39,538 (265)
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2018
Structural equation modeling (SEM) is one of the most flexible and commonly used tools in the statistical toolbox of the social scientist. Latent growth curve modeling (LGM), the subject of this chapter, is one application of SEM to the analysis of change.
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Structural equation modeling (SEM) is one of the most flexible and commonly used tools in the statistical toolbox of the social scientist. Latent growth curve modeling (LGM), the subject of this chapter, is one application of SEM to the analysis of change.
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Time to criterion latent growth models.
Psychological Methods, 2019Latent growth models, a special class of longitudinal models within the broader structural equation modeling (SEM) domain, provide researchers a framework for investigating questions about change over time; yet rarely is time itself modeled as a focal parameter of interest.
Tessa L, Johnson, Gregory R, Hancock
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Latent variable growth within behavior genetic models
Behavior Genetics, 1986The purpose of this paper is to introduce one kind of latent-variable structural-equation model for multivariate longitudinal data which includes behavioral genetic components. A generic structural-equation model termedRAM (McArdle, J. J. and McDonald, R. P. (1984).Br. J. Math. Stat.
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Latent Growth Curves within Developmental Structural Equation Models
Child Development, 1987This report uses structural equation modeling to combine traditional ideas from repeated-measures ANOVA with some traditional ideas from longitudinal factor analysis. A longitudinal model that includes correlations, variances, and means is described as a latent growth curve model (LGM).
J J, McArdle, D, Epstein
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2020
Piecewise latent growth models (PWLGMs) can be used to study changes in growth trajectory of an outcome due to an event or condition, such as exposure to treatment. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM.
Leite, Walter +2 more
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Piecewise latent growth models (PWLGMs) can be used to study changes in growth trajectory of an outcome due to an event or condition, such as exposure to treatment. When there are multiple outcomes of interest, a researcher may choose to fit a series of PWLGMs or a single parallel-process PWLGM.
Leite, Walter +2 more
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The Multigroup Multilevel Categorical Latent Growth Curve Models
Multivariate Behavioral Research, 2010Longitudinal data describe developmental patterns and enable predictions of individual changes beyond sampled time points. Major methodological issues in longitudinal data include modeling random effects, subject effects, growth curve parameters, and autoregressive residuals.
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