Latent Growth Curve Modeling - Couverture souple

Preacher, Kristopher J.; Wichman, Aaron L.; Maccallum, Robert C.; Briggs, Nancy E.

Couverture souple

ISBN 10 : 1412939550 ISBN 13 : 9781412939553

Editeur : SAGE Publications, Inc, 2008

Synopsis

Latent growth curve modeling (LGM)—a special case of confirmatory factor analysis designed to model change over time—is an indispensable and increasingly ubiquitous approach for modeling longitudinal data. This volume introduces LGM techniques to researchers, provides easy-to-follow, didactic examples of several common growth modeling approaches, and highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit.

The book covers the basic linear LGM, and builds from there to describe more complex functional forms (e.g., polynomial latent curves), multivariate latent growth curves used to model simultaneous change in multiple variables, the inclusion of time-varying covariates, predictors of aspects of change, cohort-sequential designs, and multiple-group models. The authors also highlight approaches to dealing with missing data, different estimation methods, and incorporate discussion of model evaluation and comparison within the context of LGM. The models demonstrate how they may be applied to longitudinal data derived from the NICHD Study of Early Child Care and Youth Development (SECCYD)..

Key Features

· Provides easy-to-follow, didactic examples of several common growth modeling approaches

· Highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit

· Explains the commonalities and differences between latent growth model and multilevel modeling of repeated measures data

· Covers the basic linear latent growth model, and builds from there to describe more complex functional forms such as polynomial latent curves, multivariate latent growth curves, time-varying covariates, predictors of aspects of change, cohort-sequential designs, and multiple-group models

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A propos du livre

À propos de l'auteur

Kristopher J. Preacher, Ph.D. is a Professor in the Quantitative Methods program at Vanderbilt University. His research concerns the use (and combination) of structural equation modeling and multilevel modeling to model correlational and longitudinal data. Other interests include developing techniques to test mediation and moderation hypotheses, bridging the gap between substantive theory and statistical practice, and studying model evaluation and model selection in the application of multivariate methods to social science questions. He serves on the editorial boards of Psychological Methods, Multivariate Behavioral Research, and Communication Methods and Measures.

À propos de la quatrième de couverture

Latent growth curve modeling (LGM)-a special case of confirmatory factor analysis designed to model change over time-is an indispensable and increasingly ubiquitous approach for modeling longitudinal data. This volume introduces LGM techniques to researchers, provides easy-to-follow, didactic examples of several common growth modeling approaches, and highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit.

The book covers the basic linear LGM, and builds from there to describe more complex functional forms (e.g., polynomial latent curves), multivariate latent growth curves used to model simultaneous change in multiple variables, the inclusion of time-varying covariates, predictors of aspects of change, cohort-sequential designs, and multiple-group models. The authors also highlight approaches to dealing with missing data, different estimation methods, and incorporate discussion of model evaluation and comparison within the context of LGM. The models demonstrate how they may be applied to longitudinal data derived from the NICHD Study of Early Child Care and Youth Development (SECCYD)..

Key Features

· Provides easy-to-follow, didactic examples of several common growth modeling approaches

· Highlights recent advancements regarding the treatment of missing data, parameter estimation, and model fit

· Explains the commonalities and differences between latent growth model and multilevel modeling of repeated measures data

· Covers the basic linear latent growth model, and builds from there to describe more complex functional forms such as polynomial latent curves, multivariate latent growth curves, time-varying covariates, predictors of aspects of change, cohort-sequential designs, and multiple-group models

Détails de l'édition

• Éditeur: SAGE Publications, Inc
• Date d'édition: 2008
• Langue: anglais
• ISBN 10: 1412939550
• ISBN 13: 9781412939553
• Reliure: Broché
• Nombre de pages: 96
• Coordonnées du fabricant: non disponible
• Personne responsable: GPSR Kontakt; gpsr@libri.de; ; Europaallee 1; Bad Hersfeld; 36244; Allemagne