Higher-order growth curves and mixture modeling with Mplus : a practical guide

著者

    • Wickrama, K. A. S.
    • Lee, Tae Kyoung
    • O'Neal, Catherine Walker
    • Lorenz, Frederick O. (Frederick Oscar)

書誌事項

Higher-order growth curves and mixture modeling with Mplus : a practical guide

Kandauda (K. A. S.) Wickrama, Tae Kyoung Lee, Catherine Walker O'Neal & Frederick O. Lorenz

（Multivariate applications series）

Routledge, 2022

2 [edition]

大学図書館所蔵 件 / 全2件

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注記

Content Type: text (rdacontent), Media Type: unmediated (rdamedia), Carrier Type: volume (rdacarrier)

Summary: "This practical introduction to second-order and growth mixture models using Mplus introduces simple and complex techniques through incremental steps. The authors extend latent growth curves to second-order growth curve and mixture models and then combine the two using normal and non-normal (e.g., categorical) data. To maximize understanding, each model is presented with basic structural equations, figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results. Examples from a variety of disciplines demonstrate the use of the models and exercises allow readers to test their understanding of the techniques. A comprehensive introduction to confirmatory factor analysis, latent growth curve modeling, and growth mixture modeling is provided so the book can be used by readers of various skill levels. The book's datasets are available on the web. New to this edition: - Two new chapters providing a stepwise introduction and practical guide to the

Includes bibliographical references and index

内容説明・目次

内容説明

- The first practical introduction to second-order and growth mixture models using Mplus 8.4 -Introduces simple and complex models through incremental steps with increasing complexity -Each model is presented with figures with associated syntax that highlight what the statistics mean, Mplus applications, and an interpretation of results, to maximize understanding. - Second-order and growth mixture modeling is increasingly being used in various disciplines to analyze changes in individual attributes such as personal behaviors and relationships over time

目次

1 Introduction 2 Latent Growth Curves 3 Longitudinal Confirmatory Factor Analysis and Curve-of-Factors Growth Curve Models 4 Estimating Curve-of-Factors Growth Curve Models 5 Extending a Parallel Process Latent Growth Curve Model (PPM) to a Factor-of-Curves Model (FCM) 6 Estimating a Factor-of-Curves Model (FCM) and Adding Covariates 7 An Introduction to Growth Mixture Models (GMM) 8. Estimating a Conditional Growth Mixture Model (GMM) 9 Second-Order Growth Mixture Models (SOGMMs) 10. Growth Curve Analysis with Categorical Outcomes [NEW CHAPTER] 11. Higher-order Growth Curve Analysis with Categorical Outcomes [NEW CHAPTER]

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