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Quantitative Applications in the Social Sciences #157: Latent Growth Curve Modeling

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Quantitative Applications in the Social Sciences #157: Latent Growth Curve Modeling Cover

 

Synopses & Reviews

Publisher Comments:

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

Book News Annotation:

Intended for researchers familiar with structural equation modeling, this slim text describes 12 latent growth curve models for studying change in phenomena over time, and shows how to fit models to data using LISREL, Mx, and Mplus. Specialized applications extend LGM to growth mixture models, modeling change in latent variables, autoregressive latent trajectory models, and modeling change in categorical outcomes. Annotation ©2008 Book News, Inc., Portland, OR (booknews.com)

Product Details

ISBN:
9781412939553
Author:
Preacher, Kristopher J.
Publisher:
Sage Publications (CA)
Author:
Briggs, Nancy E.
Author:
Wichman, Aaron L.
Author:
MacCallum, Robert C.
Subject:
Research
Subject:
Social sciences
Subject:
Latent variables.
Subject:
Probability & Statistics - Multivariate Analysis
Subject:
Methodology
Subject:
Social sciences -- Statistical methods.
Subject:
Longitudinal method
Subject:
Sociology-Reference and Methodology
Copyright:
Series:
Quantitative Applications in the Social Sciences
Series Volume:
157
Publication Date:
20080631
Binding:
TRADE PAPER
Language:
English
Illustrations:
Y
Pages:
96
Dimensions:
8.30x5.40x.20 in. .30 lbs.

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Related Subjects

History and Social Science » Sociology » Reference and Methodology

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