This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the reader’s familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the book’s CD. Throughout the book, 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―growth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group issues (analyzing growth in multiple populations, accelerated designs, and multi-level longitudinal approaches), and then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. 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.
This practical guide is ideal for a wide range of 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, as well as for a text on latent variable growth curve modeling or as a supplement for a course on multivariate statistics. A prerequisite of graduate level statistics is recommended.
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Terry E. Duncan is a Senior Research Scientist at the Oregon Research Institute. He received his Ph.D. from the University of Oregon and is an active researcher in statistical methods for longitudinal and multilevel designs, structural equation and generalized linear models, approaches for the analysis of missing data, and the etiology of substance use and development.
Susan C. Duncan is a Senior Research Scientist at the Oregon Research Institute. She received her Ph.D. from the University of Oregon. She is known for her work on substantive, statistical, and methodological issues related to youth health risk and health promoting behaviors.
Lisa A. Strycker is a Senior Research Associate and Co-Investigator at the Oregon Research Institute. She received her M.S. in psychology in 1997 from the University of Oregon. Her research interests include statistical methods, chronic illness, and health behaviors.
"...The book is an excellent mid-level text on latent growth modeling... [The graphics] are arguably better than those in any other book on any aspect of SEM. They are crisp and clear, and the inclusion of the theoretical weights is greatly helpful in understanding the graphics..." - Lee Sechrest, Ph.D., University of Arizona
"I initially learned growth modeling from this book, and I am still a big fan. It allowed me to jump in and get my feet wet with this flexible analytic method...the text really is just as its title suggestsan introduction–and an excellent one at that...." - James A. Bovaird, Ph.D., University of Kansas
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Paperback. Condition: new. Paperback. This book provides a comprehensive introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. It presents the statistical basis for LGM and its various methodological extensions, including a number of practical examples of its use. It is designed to take advantage of the readers familiarity with analysis of variance and structural equation modeling (SEM) in introducing LGM techniques. Sample data, syntax, input and output, are provided for EQS, Amos, LISREL, and Mplus on the books CD. Throughout the book, 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 chaptersgrowth modeling with ordered categorical variables, growth mixture modeling, and pooled interrupted time series LGM approaches. Following a new organization, the book now covers the development of the LGM, followed by chapters on multiple-group issues (analyzing growth in multiple populations, accelerated designs, and multi-level longitudinal approaches), and then special topics such as missing data models, LGM power and Monte Carlo estimation, and latent growth interaction models. 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.This practical guide is ideal for a wide range of 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, as well as for a text on latent variable growth curve modeling or as a supplement for a course on multivariate statistics. A prerequisite of graduate level statistics is recommended. This book provides an introduction to latent variable growth curve modeling (LGM) for analyzing repeated measures. Designed to take advantage of the readers 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780805855470
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