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Grimm, Kevin; Zhang, Zhiyong; Hamagami, Fumiaki; Mazzocco, Michele – Multivariate Behavioral Research, 2013
We propose the use of the latent change and latent acceleration frameworks for modeling nonlinear growth in structural equation models. Moving to these frameworks allows for the direct identification of "rates of change" and "acceleration" in latent growth curves--information available indirectly through traditional growth…
Descriptors: Structural Equation Models, Change, Individual Differences, Mathematics Skills
Bianconcini, Silvia – Multivariate Behavioral Research, 2012
In the SEM literature, simplex and latent growth models have always been considered competing approaches for the analysis of longitudinal data, even if they are strongly connected and both of specific importance. General dynamic models, which simultaneously estimate autoregressive structures and latent curves, have been recently proposed in the…
Descriptors: Structural Equation Models, Longitudinal Studies, Academic Achievement, Higher Education
Alessandri, Guido; Caprara, Gian Vittorio; Tisak, John – Multivariate Behavioral Research, 2012
Literature documents that the judgments people hold about themselves, their life, and their future are important ingredients of their psychological functioning and well-being and are commonly related to each other. In this article, results from a longitudinal study (N = 298, 45% males) are presented. Using an integrative Latent Curve, Latent…
Descriptors: Statistical Analysis, Adolescents, Personality Traits, Individual Development
Imai, Kosuke; Jo, Booil; Stuart, Elizabeth A. – Multivariate Behavioral Research, 2011
In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by…
Descriptors: Research Design, Statistical Analysis, Research Methodology, Longitudinal Studies
Reichardt, Charles S. – Multivariate Behavioral Research, 2011
Maxwell, Cole, and Mitchell (2011) demonstrated that simple structural equation models, when used with cross-sectional data, generally produce biased estimates of meditated effects. I extend those results by showing how simple structural equation models can produce biased estimates of meditated effects when used even with longitudinal data. Even…
Descriptors: Structural Equation Models, Statistical Data, Longitudinal Studies, Error of Measurement
Choi, Jaehwa; Harring, Jeffrey R.; Hancock, Gregory R. – Multivariate Behavioral Research, 2009
Throughout much of the social and behavioral sciences, latent growth modeling (latent curve analysis) has become an important tool for understanding individuals' longitudinal change. Although nonlinear variations of latent growth models appear in the methodological and applied literature, a notable exclusion is the treatment of growth following…
Descriptors: Causal Models, Structural Equation Models, Longitudinal Studies, Change
Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S. – Multivariate Behavioral Research, 2012
A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…
Descriptors: Monte Carlo Methods, Computation, Robustness (Statistics), Structural Equation Models
Grimm, Kevin J.; Pianta, Robert C.; Konold, Timothy – Multivariate Behavioral Research, 2009
Multitrait-multimethod (MTMM) confirmatory factor models were combined with longitudinal structural equation models to examine trait and method stability over time. A longitudinal correlated-trait correlated-method (CT-CM) model allowed for the study of trait and method variance in observed scores over time. Longitudinal measurement invariance was…
Descriptors: Multitrait Multimethod Techniques, Structural Equation Models, Longitudinal Studies, Children
Harring, Jeffrey R.; Cudeck, Robert; du Toit, Stephen H. C. – Multivariate Behavioral Research, 2006
The nonlinear random coefficient model has become increasingly popular as a method for describing individual differences in longitudinal research. Although promising, the nonlinear model it is not utilized as often as it might be because software options are still somewhat limited. In this article we show that a specialized version of the model…
Descriptors: Computer Software, Structural Equation Models, Individual Differences, Longitudinal Studies

McArdle, John J. – Multivariate Behavioral Research, 1994
Benefits and limitations of structural equation models for multivariate experiments with incomplete data are presented. Examples from studies of latent variable path models of cognitive performance illustrate analyses with latent variables, omitted variables, randomly missing data, and nonrandomly missing data. (SLD)
Descriptors: Cost Effectiveness, Experiments, Factor Analysis, Longitudinal Studies

Duncan, Susan C.; Duncan, Terry E. – Multivariate Behavioral Research, 1994
Using an approach to the analysis of missing data, this study investigated developmental trends in alcohol, marijuana, and cigarette use among 750 adolescents across 5 years using multiple-group latent growth modeling. Latent variable structural equation modeling and missing data approaches to studying developmental change are explored. (SLD)
Descriptors: Adolescents, Change, Child Development, Drinking

Raykov, Tenko – Multivariate Behavioral Research, 1995
The ability of 248 older adults to improve their performance on fluid intelligence tests, with or without tutor-guided instruction in cognitive skills, was studied using multidimensional longitudinal structural equation models. Results suggest considerable plasticity in adult intellectual function and the capacity to improve performance. (SLD)
Descriptors: Change, Cognitive Processes, Intellectual Development, Intelligence Tests