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Latent Growth Curve Modeling

Kristopher J. Preacher, Nancy E. Briggs · 2008

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About the book

"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)."--pub. desc.

Book details

Year
2008
Language
English
Series
Quantitative applications in the social sciences -- 157
Publisher
Sage Publications
Editions
5
Pages
112
ISBN
9781412939553

Data source: Wikidata

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