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Latent growth curve modeling (LGM)a special case of confirmatory factor analysis designed to model change over timeis an indispensable and increasingly ubiquitous approach for modeling longitudinal data. This volume introduces LGM techniques to researchers, provides easytofollow, 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 timevarying covariates, predictors of aspects of change, cohortsequential designs, and multiplegroup 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 easytofollow, 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, timevarying covariates, predictors of aspects of change, cohortsequential designs, and multiplegroup modelsLearn more about "The Little Green Book" QASS Series! Click Here
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birth defects, or other reproductive harm.
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