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Discovering Structural Equation Modeling Using Stata: Revised Edition by Alan C. Acock

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Description

Discovering Structural Equation Modeling Using Stata, Revised Edition is devoted to Stata's sem command and all it can do. Learn about its capabilities in the context of confirmatory factor analysis, path analysis, structural equation modeling, longitudinal models, and multiple-group analysis. Each model is presented along with the necessary Stata code, which is parsimonious, powerful, and can be modified to fit a wide variety of models. The datasets used are downloadable, offering a hands-on approach to learning.

A particularly exciting feature of Stata is the SEM Builder. This graphical interface for structural equation modeling allows you to draw publication-quality path diagrams and fit the models without writing any programming code. When you fit a model with the SEM Builder, Stata automatically generates the complete code that you can save for future use. Use of this unique tool is extensively covered in an appendix and brief examples appear throughout the text.



About the Author

Alan C. Acock is a sociologist and a University Distinguished Professor in the School of Social and Behavioral Health Sciences at Oregon State University. He was also recognized as the Alumni Distinguished Professor based on his work with students. He has published more than 130 articles in leading journals across the social and behavioral sciences, including Structural Equation Modeling, Psychological Bulletin, Multivariate Behavioral Research, Journal of Gerontology, Journal of Adolescence, American Journal of Public Health, American Sociological Review, Journal of Marriage and Family, Social Forces, Educational and Psychological Measurement, Journal of Politics, Prevention Science, and American Journal of Preventive Medicine. He also authored the text A Gentle Introduction to Stata.




Book Information
ISBN 9781597181396
Author Alan C. Acock
Format Paperback
Page Count 306
Imprint Stata Press
Publisher Stata Press
Weight(grams) 657g

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