Latent Growth Curve Modeling

Nonfiction, Reference & Language, Reference, Research, Social & Cultural Studies, Social Science
Cover of the book Latent Growth Curve Modeling by Aaron Lee Wichman, Dr. Kristopher J. Preacher, Dr. Nancy E. Briggs, Robert Charles MacCallum, SAGE Publications
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Author: Aaron Lee Wichman, Dr. Kristopher J. Preacher, Dr. Nancy E. Briggs, Robert Charles MacCallum ISBN: 9781506333052
Publisher: SAGE Publications Publication: June 27, 2008
Imprint: SAGE Publications, Inc Language: English
Author: Aaron Lee Wichman, Dr. Kristopher J. Preacher, Dr. Nancy E. Briggs, Robert Charles MacCallum
ISBN: 9781506333052
Publisher: SAGE Publications
Publication: June 27, 2008
Imprint: SAGE Publications, Inc
Language: English

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

Learn more about "The Little Green Book" - QASS Series! Click Here

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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

Learn more about "The Little Green Book" - QASS Series! Click Here

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