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An Introduction to Latent Variable Growth Curve Modeling - Concepts, Issues, and Application, Second Edition (Paperback, 2nd edition)
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An Introduction to Latent Variable Growth Curve Modeling - Concepts, Issues, and Application, Second Edition (Paperback, 2nd edition)
Series: Quantitative Methodology Series
Expected to ship within 10 - 15 working days
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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
quantitativemethodologists, 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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