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Structural Equation Modeling: Applications Using Mplus: Methods and Applications (Wiley Series in Probability and Statistics)
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Product Details
- A reference guide for applications of SEM using MplusStructural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a reference guide. Written in non-mathematical terms, this book focuses on the conceptual and practical aspects of Structural Equation Modeling (SEM). Basic concepts and examples of various SEM models are demonstrated along with recently developed advanced methods, such as mixture modeling and model-based power analysis and sample size estimate for SEM. The statistical modeling program, Mplus, is also featured and provides researchers with a flexible tool to analyze their data with an easy-to-use interface and graphical displays of data and analysis results.Key features:Presents a useful reference guide for applications of SEM whilst systematically demonstrating various advanced SEM models, such as multi-group and mixture models using Mplus.Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes.Provides step-by-step instructions of model specification and estimation, as well as detail interpretation of Mplus results.Explores different methods for sample size estimate and statistical power analysis for SEM.By following the examples provided in this book, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book.
| Publisher | John Wiley & Sons Inc |
| Publication date | January 1, 2012 |
| Edition | 3rd |
| Language | English |
| Print length | 453 pages |
| ISBN-10 | 1119978297 |
| ISBN-13 | 978-1119978299 |
| Item Weight | 1.64 pounds (740 grams) |
| Dimensions | 6 x 1 x 9.25 inches (15.2 x 2.5 x 23.5 cm) |
Product Description
Structural Equation Modeling: Applications Using Mplus: Methods and Applications (Wiley Series in Probability and Statistics)
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