Introduction to Latent Variable Growth Curve Modeling, an: Concepts, Issues, and Applications, Second Edition |
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Author:
| Duncan, Susan C. |
ISBN: | 978-1-282-37366-2 |
Publication Date: | Jan 2006 |
Publisher: | Taylor & Francis Group
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Book Format: | Ebook |
List Price: | USD $80.00 |
Book Description:
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This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. Designed to take advantage of the reader s familiarity with ANOVA and SEM in introducing LGM techniques, the book presents the statistical basis for LGM and its various methodological extensions and practical examples of its use. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book s CD. The authors present a variety...
More DescriptionThis book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. Designed to take advantage of the reader s familiarity with ANOVA and SEM in introducing LGM techniques, the book presents the statistical basis for LGM and its various methodological extensions and practical examples of its use. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book s CD. The authors present a variety of LGM techniques that are useful for many different research designs and numerous figures provide helpful diagrams of the examples. Updated throughout, the second edition features three new chapters and a new organization. The model specifications previously included in the appendices are now available on the CD so the reader can more easily adapt the models to their own research. Ideal for social and behavioral researchers interested in the measurement of change over time, including social, developmental, organizational, educational, consumer, personality and clinical psychologists, sociologists, and quantitative methodologists, the book also serves as a text on latent variable growth curve modeling. A prerequisite of graduate level statistics is recommended."